Supply Chain Network Design & logistics

Application of fuzzy goal programming and genetic algorithm is considered in this paper. We extend a multi-objective model for integrated inventory-production-distribution planning in supply chain (SC). We consider a supply chain network which consists of a manufacture, with multiple plants, multiple distribution centers (DCs), multiple retailers and multiple customers. The manufacturer produces several items. Decision maker's imprecise aspiration levels of goals are incorporated into model using fuzzy goal programming approach. Due to the complexity of problem in large size and in order to get a satisfactory near optimal solution with great speed, a new genetic algorithm is proposed to solve constrained problems. To show the efficiency of the used model and fuzzy goal programming approach and genetic algorithm for the collaborative inventory-production-distribution problem, computational experiments are performed on a hypothetically constructed case problem.

The business environment, especially in the supply chain, is virtually fluctuating and is entangled with a lot of problems. Accordingly, a tailored mechanism should be adopted to deal with these problems. To do so, supply chains must take precautionary measures such as storing products and holding safety stock, etc. Given the importance of storage in supply chains, warehouses and depots should be carefully taken into account and located in such a way that their best performance is warranted. In this regard, this paper addresses a robust Multi-Objective multi-product model to design a distribution system under operational risks and disruption considerations. In the proposed model, the objective functions include minimizing the total distribution system cost, the total environmental impacts caused by supply chain along with minimizing the maximum lost sales in customer zones, while taking into consideration possible complete multiple disruptions in facilities and routes between them. Besides, a ε-constraint method is utilized to convert the Multi-Objective problem to a single objective model. In this paper, a two-stage robust possibilistic programming approach is deployed to cope with the uncertainty and disruption risks in the proposed model. Eventually, a real automotive case study is applied to the proposed model, via which the applicability and performance of the proposed model are endorsed. Results indicate that considering operational and disruption risks in the supply chain using twostage robust optimization will require high costs but it will lead to economic savings and technical advantages in the long term.

In many industries supply chain flexibility is becoming a more and more important concept for gaining competitive advantages. By the design and use of strategic supply chain networks significant improvements of supply chain flexibility can be achieved. The article identifies resources, objects and parameters of supply chain flexibility and highlights the potentials of a strategic supply chain network to realize high supply chain flexibility. The findings are relevant for both scientists and practitioners, who are interested in supply chain management. It is demonstrated how to manage the structural, technological and human potentials of the strategic supply chain network to gain outstanding supply chain flexibility.

We consider an optimization problem that models the integrated production and preventive maintenance planning at the tactical level in a manufacturing system. Along the same lines as in the recent models, which were proposed for this planning problem, this integration is carried out via available production capacity. This model in particular, considers explicitly the fact that the degradation of the machine takes place only when this latter is put to production. A mathe-matical programming model is proposed that accurately models the integrated production and preventive maintenance planning problem. Benders decomposition approach is then used to solve it, as this besides its complications, has some interesting features. Some numerical experiments are carried out on a set of test instances which are usually used for lot-sizing problems. The obtained preliminary results are presented and discussed in detail.

Global sourcing operates under the challenges and pressures of intensive global-wide competition. Global sourcing can benefit from the functionality of electronic business (EB) by exhibiting more flexible structures and added opportunities in communications and transactions with partners among worldwide supply chains/networks. This study aims to answer two research questions, "what are the relationships between global sourcing and EB?" and "how do EB applications and strategies help global sourcing lead to better performance?" Our literature review addresses the relationships between global sourcing and EB from three perspectives: the applied theories, the covered business scope, and the changing roles of flows. In analyzing the potential benefits of EB to global sourcing, the enhancement on SC components and alignment effects are discussed. Finally, a framework is proposed to highlight how EB and global sourcing interact with each other, resulting in five major issues: the enhancement of SC components, the changing micro-environment, the effect of accelerating evolution of global sourcing, the integration of activities, and the significant improvement on outcomes.

The sustainability of the logistics sector is challenged by its energy consumption, pressures on GHG emissions, globalisation, increased competition and consumer behaviour changes. In order to address these challenges, logistics actors have started to implement environmentally friendly collaborative strategies addressing supply chain integration, multimodal transport, consolidation of deliveries and reverse logistics. The implementation of such strategies frequently asserts the need for proactive and reactive coordination based on information sharing between collaborating actors, to optimally match supply and demand for logistics resources. However, adoption of advanced collaborative ICT solutions by the logistics sector is hindered by the number of transport management solutions, which yields a fragmented story, where actors have to contend with multiple tools, relationships, and fragmented views of their logistics business which are difficult, or impossible, to unify into one pers...

This paper establishes the need for Supply Chain Performance Measure through the review of available literature on supply chain. The evaluation of various performance measure frameworks and metrics already available suggests that supply chain performance measure can be observed under various categories such as cost and non-cost; strategic and operational level; financial and business process perspective; customer, financial, internal operation, learning and growth perspective. The core features and limitations in various performance metrics available for the selection and adoption by business organisations have been analysed. The limitations of these frameworks suggest that companies should select and implement one or more metrics depending upon the nature of their business and its supply chain. It is also comprehended from literature that there is a need for integration of IT in supply chain performance measurement. Since the already present frameworks are quite generalised, this p...

The supply chain is considered one of the key areas of companies’ success and it should be designed appropriately to be compatible with companies’ objectives and strategies. In this thesis, a supply chain network redesign case study in the oil and gas industry will be thoroughly studied, analyzed, and concluded. This research has been applied and deployed on an oil and gas local company called “X-LUBE”.  In brief, the Multi-Criteria Decision Making (MCDM) approach is used to develop the best transportation setup for X-LUBE distribution network among five available alternatives, which are compared using predefined criteria. Several MCDM techniques were used such as AHP, TOPSIS, PROMETHEE, and ELCTRE. Similarly; AHP technique was used to determine the expansion plan and strategies of the X-LUBE distribution network along with associated cost and fleet type selection

This research investigates how information and material distortions affect the inventory management performance of a major retailer. Bullwhip effects (BWEs) are individually calculated for dozens of products carried by dozens of retail locations. Relationships between item/store-level BWEs and item/store-level performance measures including gross margins and inventory levels are tested and reported.

For decades, due to the increasing generation of waste and its negative environmental impacts, efficient municipal solid waste management (MSWM) has become a major concern of sustainable development. On the other hand, selecting an appropriate strategy remains a critical issue for municipal authorities without applying a multi-criteria decision-making (MCDM) approach. This study aims to select the best MSWM strategy from five potential MSW management strategies under various factors that influence waste strategy selection, such as economic, social, technical, and environmental factors. This study used three fuzzy integrated MCDM methods, namely the Decision-Making Trail and Evaluation Laboratory (DMATEL), the Analytic Network Process (ANP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to select best MSWM strategies. The study used data from a survey of experts who had knowledge of waste management. The survey data was then analyzed using the DMATEL, ANP and TOPSIS methods under a fuzzy environment. The Fuzzy DEMATEL method is used to identify the causal relationships among the criteria and sub-criteria, while ANP is applied to determine the relative weights of MSWM strategy selection sub-criterion. Finally, TOPSIS is used to rank the waste management strategies depending on established sub-criteria. The result of fuzzy TOPSIS demonstrated that recycling of municipal solid waste is the best alternative which has the highest closeness coefficient followed by reuse. Thus, the result of this study revealed that MSWM strategies are ranked as: waste recycling (A1), reuse (A2), reduce (A1), energy recovery (A4), and disposal (A5), with closeness coefficient values of 0.80, 0.61, 0.60, 0.47, and 0.17, respectively.

The pandemic and a series of subsequent disruptive events fully exposed the vulnerability of supply chains. Research in the field of resilience in supply chain risk management has recorded significant interest across a wide range of academic disciplines. Therefore, there is a need to synthesize, categorize and explain existing and newly emerging research directions, which may represent relevant platforms for developing supply chain concepts in the future. This study addresses this need by providing a bibliometric review of published papers on resilience in supply chain risk management. By analyzing more than 2500 published papers through bibliometric and machine-learning-based methods, we identified ten topics related to risk and resilience of supply chains: Pandemic impacts of food supply chain; Practices for capability and performance; Supplier-related modeling and optimization; System security and critical infrastructure; Production changes; IT in manufacturing process; Sustainability in global economy; Management and business approach; Modeling and design of complex networks; Operational strategies for risk mitigation. By analyzing articles published since 2020, we also identified a change in the direction of research dedicated to supply chain risk and resilience; we identified three other topics that were not recognized as distinct topics prior to 2020—Operational management; strategy; Sustainable production. The results of this study help in understanding the change in the direction of research in the area of risk and resilience of supply chains and thus provide up-to-date information for further research in this dynamically developing area.

Application of fuzzy goal programming and genetic algorithm is considered in this paper. We extend a multi-objective model for integrated inventory-production-distribution planning in supply chain (SC). We consider a supply chain network which consists of a manufacture, with multiple plants, multiple distribution centers (DCs), multiple retailers and multiple customers. The manufacturer produces several items. Decision maker's imprecise aspiration levels of goals are incorporated into model using fuzzy goal programming approach. Due to the complexity of problem in large size and in order to get a satisfactory near optimal solution with great speed, a new genetic algorithm is proposed to solve constrained problems. To show the efficiency of the used model and fuzzy goal programming approach and genetic algorithm for the collaborative inventory-production-distribution problem, computational experiments are performed on a hypothetically constructed case problem.

Ce sommaire exhaustif explore les fondements essentiels de la logistique et du commerce international, en commençant par les concepts de base qui sous-tendent la gestion efficace des flux de biens et services à travers le monde. Il examine en détail la définition de la logistique, la gestion de la chaîne d'approvisionnement, la logistique internationale et les Incoterms, ainsi que les principes fondamentaux de gestion des stocks, du transport et de la distribution. En parallèle, il analyse les théories classiques comme l'avantage absolu et l'avantage comparatif, ainsi que les théories modernes telles que le modèle Heckscher-Ohlin et l'économie d'échelle, qui structurent le paysage théorique du commerce international.

Le document explore également les politiques cruciales qui façonnent le commerce international, en confrontant le protectionnisme et le libre-échange. Il détaille les instruments et les arguments pour et contre chaque politique, fournissant une vue d'ensemble complète des régulations commerciales qui influencent les stratégies nationales et internationales. En outre, il met en lumière les institutions clés telles que le GATT et l'OMC, leur rôle historique, leurs objectifs et leurs contributions à la régulation et à la résolution des différends dans le commerce mondial.

Enfin, ce sommaire prépare les lecteurs aux défis contemporains et aux opportunités émergentes dans le domaine de la logistique et du commerce international. Il aborde les innovations technologiques, la durabilité, la gestion des risques dans les chaînes d'approvisionnement, ainsi que les tendances économiques et géopolitiques actuelles. En offrant un profil complet du secteur, il inspire une vision stratégique pour les professionnels aspirant à naviguer dans un environnement mondial en constante évolution.

Son 60-70 yıldır, akademik ve pratik alanlarda, deterministik yerine, bulanık / olabilirlikli matematiksel programlama yöntemleri geliştirilerek daha etkin ve uygulanabilir çözümler elde edilmeye çalışılmaktadır. Belirsizlik ortamında; Çok Amaçlı Karar Verme yaklaşımlarıyla, belirli tatmin seviyeleri için uzlaşık çözümler bulunabilmektedir. Ayrıca, karar verici, Etkileşimli Çok Amaçlı Karar Verme yaklaşımlarıyla, kaynakların kullanımına bağlı olarak hedeflerin tatmin seviyeleri ve uzlaşık çözümlerdeki değişiklikleri ortaya koyabildiğinden, ödünleşme kararlarında birçok alternatife sahip olmakta ve bu sayede daha esnek karar verme imkânı bulmaktadır. Bu çalışmada, "Etkileşimli Bulanık / Olabilirlikli Tek / Çok Amaçlı Matematiksel Programlama" yaklaşımlarına genel bir bakış sunulmaktadır. Aynı zamanda, çeşitli kombinasyonlarda kullanılabilen bu temel yaklaşımların üstünlükleri ile bunlara duyulan ihtiyaç, gerekçeleri ile belirtilmekte ve karar vericilerin gerçek dünyada bu yaklaşımları neden dikkate alması ve kullanması gerektiği hususu vurgulanmaktadır. Bulanık / Olabilirlikli belirsizliğini çok amaçlı ve etkileşimli yaklaşımlarla birleştiren gerçek dünya çalışmalarında bir eksiklik mevcuttur. Bu bağlamda, farklı alan / sektör uygulamaları ile literatüre önemli katkılar yapılabileceği değerlendirilmektedir.

Serious game and virtual-based environments have recently been used in business contexts to promote training of business related competences as is the case of business process modeling. Due to its characteristics modern BPM methods rely heavily on computers, since they are used as a tool for model, simulate and analyze a process and its effects on the organizations. Several authors argue that these approaches offer several limitations with respect to the modeling processes namely, they typically offer a low degree of collaboration between users, the simulations are simplistic and do not take into account the possible interaction of users during the simulation process and the interfaces are many time complex and abstract requiring an extensive training in order to use those tools. Serious games and virtual environments are mentioned as a promising approach for teaching and simulating BPM since due to their characteristics they can solve or minimize many of those limitations. In this paper we describe a serious game named ImPROVE for teaching business process modeling in a realworld context, the Manchester triage system. The simulation layer of the game was based on Time-based Activity-based Costing which also provides feedback information related to costing of activities in a business process.

Many cities and towns offer nowadays to citizens a bike sharing system (BSS). When a company starts the service, several decisions have to be taken on the location and size of the rental stations, and the number of vehicles to use to re-balance the bikes in the stations, in addition to the cost and policies for the payment of the service. Also, when the service is in place, it is often necessary to modify it, in many cases to expand it. In this paper, starting from the experience gained in a real-case application, we present a simulation framework to support the tactical decisions in the design or revision of a BSS. We will also present the application of the framework to the case of Bicimia in Brescia, Italy.

Betweenness Centrality (BC) has proven to be a fundamental metric in many domains to identify the components (nodes) of a system modelled as a graph that are mostly traversed by information flows thus being critical to the proper functioning of the system itself. In the transportation domain, the metric has been mainly adopted to discover topological bottlenecks of the physical infrastructure composed of roads or railways. The adoption of this metric to study the evolution of transportation networks that take into account also the dynamic conditions of traffic is in its infancy mainly due to the high computation time needed to compute BC in large dynamic graphs. This paper explores the adoption of dynamic BC,i.e.,BC computed on dynamic large-scale graphs, modeling road networks and the related vehicular traffic, and proposes the adoption of a fast algorithm for ahead monitoring of transportation networks by computing approximated BC values under time constraints. The experimental an...

In economic model predictive control (EMPC), the standard quadratic objective function of MPC is replaced with an economic objective such that the controller directly optimizes the economic performance of the plant. However, economic objective functions are likely to be monotone in some input direction, and this will typically lead to operation with constraints active. Operating the plant with active constraints is not economically robust; even small disturbances or errors could cause constraint violations which may lead to large costs. In this paper we address this issue by adding margins to the constraints in order to force the plant to operate in the interior of the feasible set, thereby providing some robustness to uncertainty. To determine the magnitude of these margins, we introduce an outer loop which optimizes the margins online based on measurements of the closed-loop economic performance. Our approach is simple to implement and introduces essentially no computational overhead as compared to the nominal EMPC problem. In addition, only minimal knowledge of the uncertainties present in the system is required.

The asymmetric demand-offer problem represents a major challenge for one-way vehicle sharing systems (VSS) affecting their economic viability as it necessitates the engagement of considerable human (and financial) resources in relocating vehicles to satisfy customer demand. In this paper, we propose a novel approach which involves user-based vehicle relocations to address supplyand-demand mismatches; in our approach, VSS users are offered price incentives so as to accept picking up their vehicle from an oversupplied station and/or to drop it off to an under-supplied station. The system incentivizes users based on the priorities of vehicle relocations among stations, taking into account the fluctuating demand for vehicles and parking places at different stations over time. A graph-theoretic approach is employed for modeling the problem of allocating vehicles to users in a way that maximizes the profit of the system taking into account the budget the VSS can afford to spend for rewarding users, as well as the users' strategic behavior. We present two different schemes for incentivizing users to act in favour of the system. Both schemes consider budget constraints and are truthful and budget-feasible. We have extensively evaluated our approach through simulations which demonstrated significant gain with respect to the number of completed trips and system revenue. We have also validated our approach through pilot trials conducted in a free-floating e-motorbike sharing system in the framework of an EUfunded research project.

Supply chain network design (SCND) is one of the important, primary and strategic decisions affecting competitive advantages and all other decisions in supply chain management. Although most of papers in SCND focus only on the economic performance, this study considers simultaneously economic, social and environmental aspects. In this study, a new mixed integer nonlinear programming model is developed to formulate a multi-objective sustainable closed-loop supply chain network design problem by considering discount supposition in the transportation costs for the first time. In order to address the problem, not only traditional and recent metaheuristics are utilized, but also the algorithms are hybridized according to their strengths especially in intensification and diversification. To evaluate the efficiency and effectiveness of these algorithms, they are compared with each other by four assessment metrics for Pareto optimal analyses. Although the results indicate the performance of three proposed new hybridization algorithms, KAGA achieves better solutions compared with the others, but it needs more time. At the end, we introduced a real industrial example in glass industry to verify the proposed model and the algorithms. Keywords Multi-objective optimization Á Metaheuristics Á Hybrid methods Á Closed-loop supply chain Á Sustainable developments Á Discount Neural Computing and Applications

In this paper, for effective multi-echelon supply chains under stochastic and fuzzy environments, an inventory management framework and deterministic/stochastic-neuro-fuzzy cost models within the context of this framework are structured. Then, a numerical application in a three-echelon tree-structure chain is presented to show the applicability and performance of proposed framework. It can be said that, by our framework, efficient forecast data is ensured, realistic cost titles are considered in proposed models, and also the minimum total supply chain cost values under demand, lead time and expediting cost pattern changes are presented and examined in detail.

In this paper, we study a strategic facility location problem under uncertainty. The uncertainty associated with future events is modeled by defining alternative future scenarios with probabilities. We present a new model called the α-reliable meanexcess model that minimizes the expected regret with respect to an endogenously selected subset of worst-case scenarios whose collective probability of occurrence is no more than 1 − α. Our mean-excess risk measure is coherent and computationally efficient. Computational experiments also show that the α-reliable mean-excess criterion matches the α-reliable minimax criterion closely.

It is a well-known fact that a lot of problems have arisen during the construction projects implementation; out of which, the main distinctive problem is cost overruns. Cost overruns are evidently frequent problems in the construction industries of many developed and developing countries. Once the construction projects implementation begins, the project's costs rarely remain static. There is need for cost control on the part of contractor in order to guarantee profit and ensure the continued achievement of long term goals of the company. This study was therefore carried out to examine the post contract cost management practices of contractors in Nigeria. The study examined the frequency of use of contractor’s cost control methods and their effectiveness. A cross-sectional survey research design was adopted for the study. A structured questionnaire was used as the principal instrument for collecting data from respondents. Random sampling method was used to drawn up sample from th...

Along with information technology adoption, supply chain coordination through information sharing activities has become essential to achieve supply chain effectiveness and resilience. This paper presents the results of an empirical study investigating the moderating roles of information technology link and information sharing on the relationship between supplier development, knowledge absorption from customers, and supply chain performance. Statistical techniques such as measurement test, correlation analysis, and regression analysis are applied to analyze the data collected during the Round 4 of the High Performance Manufacturing (HPM) Project. The data sample includes 304 manufacturing plants operating in 13 countries including Brazil, China, Finland, German, Italy, Israel, Japan, Korea, Spain, Sweden, Taiwan, United Kingdom, and Vietnam. Analytical results indicate that a supply chain would perform better when focal firms invest their effort in supplier development and knowledge ...

This paper explores the dynamic landscape of supply chain processes in the contemporary era, marked by the predominance of their deep digital transformation, primarily driven by Artificial Intelligence (AI). The integration of AI into supply chain processes presents a dual challenge, necessitating the incorporation of algorithms into Information Systems (IS) while accommodating the inherent complexity and uncertainty in these processes within the rapidly disruptive changes. Despite efforts to develop unified AI integration frameworks, current literature lacks a comprehensive standardized procedure, especially in supply chain research. This paper aims to tie this gap by introducing a unified, holistic framework for integrating AI into organizational and industrial processes amidst its deep digital transformation. To demonstrate its applicability in an industrial setting, this paper examines a case study within the French Electrical Industry to illustrate how the proposed framework can be applied.

Today’s third level students are of a virtual generation, where online interactive multi-player games, virtual reality and simulations are a part of everyday life, making gaming and simulation a very important catalyst in the learning process. Teaching methods have to be more innovative to help students understand the complexity of decisions within dynamic supply chain environment. Interactive simulation games have the potential to be an efficient and enjoyable means of learning. A serious interactive business game, Automobile Supply Chain Management Game (AUSUM), has been introduced in this paper. Using theories learnt in class as a knowledge base, participants have to develop effective supply chain partnership strategy to enhance their supply chain networks. Deploying the game over the web encourages student interaction and group work. Most importantly the game will enable students to fundamentally grasp the impact of strategic decisions on other parts and players of the supply ch...

This is an era marked by rapid technology development in all different educational arenas. Alongside this growing demand of technology, learning process is getting new forms and hence traditional teaching approaches tend to struggle and lack the requisite qualities to meet new generation expectations. In third level education, this problem is increasing in magnitude and new dimensions, especially when it comes to teaching difficult subjects such as supply chain management. Understanding the complexity of supply chain networks and how to manage them create a considerable level of difficulty for students and professionals. Collaboration between supply chain members is now recognised as an important strategic factor in creating a solution to the complexity of the supply chain system. New technologies are beginning to bring a huge transformation into teaching delivery methods. This paper presents an integrated web-based simulation framework that supports learning supply chain concepts a...

The emerging eLearning paradigm is becoming increasingly used in many academic disciplines. The concept acknowledges learning processes that no longer deploy only traditional teaching methods. It can be argued that today’s third level education students are part of a new virtual era where the blackboard has been replaced by the interactive whiteboard, so more interactive and virtually orientated teaching aids are required to assist in the transition from traditional learning to eLearning. The key objective of this paper is to propose a simulation-based learning framework that integrates web-based simulation and a web content management hierarchy model. Using the highly complex subject of supply chain management as a field of study, the newly developed eSimulation tool allows users to examine various management strategies in real-life scenarios, encourages group work and offers remote access capabilities for distance learning. Interactive learning is facilitated using a web-based por...

Today's third level students are of a virtual generation, where online interactive multi-player games, virtual reality and simulations are a part of everyday life, making gaming and simulation a very important catalyst in the learning process. Teaching methods have to be more innovative to help students understand the complexity of decisions within dynamic supply chain environment. Interactive simulation games have the potential to be an efficient and enjoyable means of learning. A serious interactive business game, Automobile Supply Chain Management Game (AUSUM), has been introduced in this paper. Using theories learnt in class as a knowledge base, participants have to develop effective supply chain partnership strategy to enhance their supply chain networks. Deploying the game over the web encourages student interaction and group work. Most importantly the game will enable students to fundamentally grasp the impact of strategic decisions on other parts and players of the supply chain network.

This paper investigates when do slotting fees arise as outcomes of the bargaining process between manufacturers and retailers. An asymmetric Nash bargaining model is used to investigate the economics of slotting fees obtained from bilateral negotiations about two-part tariff contracts. The analysis applies to an arbitrary number of manufacturers and retailers, and holds under general technology and product differentiation conditions. We show how scale economies in retail revenue and complementarity contribute to the existence of slotting fees. Such results apply irrespective of the retailer bargaining power. They indicate that observed variations in the existence and magnitude of slotting fees across products and market conditions are driven by variations in complementarity and economies of scale in retail revenue.

Whilst there is significant research on supply chain finance, there is little information about its application to the omnichannel logistics. Hence, the primary adopted goal is to identify the ways of supporting the implementation and development of SSCM with use of Artificial Intelligence and developed SSCF implementation model. Potential paths to improve supply chain’s sustainability based on SSCF and AI are presented on the example of two internationally operating companies from the clothing industry using omnichannel. An exploratory case study has been conducted. Three methods were used to gather data: document/reports analysis, direct and participative observation and unstructured interviews. By implementing AI, supply chain leaders can more easily improve all key dimensions of sustainability, especially in the strategic field, based on strengthening partnership and cooperation with suppliers offering value-added materials that guarantee a competitive advantage. The paper contr...

In this paper, we propose a rigorous dynamic supernetwork theory for the integration of social networks with financial networks with intermediation in the presence of electronic transactions. We consider decision-makers with sources of funds, financial intermediaries, as well as demand markets for the various financial products. Through a multilevel supernetwork framework consisting of the financial network and the social network we model the multicriteria decision-making behavior of the various decision-makers, which includes the maximization of net return, the maximization of relationship values, and the minimization of risk. Increasing relationship levels in our framework are assumed to reduce transaction costs as well as risk and to have some additional value for the decision-makers. We explore the dynamic evolution of the financial flows, the associated product prices, as well as the relationship levels on the supernetwork until an equilibrium pattern is achieved. We provide some qualitative properties of the dynamic trajectories, under suitable assumptions, and propose a discrete-time algorithm which is then applied to track the evolution of the relationship levels over time as well as the financial flows and prices. The equilibrium pattern yields, as a byproduct, the emergent structure of the social and financial networks since it identifies not only which pairs of nodes will have flows but also the size of the flows, i.e., the relationship levels and the financial transactions.

We consider the problem faced by a retailer that selects the set of products to allocate in finite capacity stores to maximize patronage. The purchase decision is made by customers that purchase exactly one product that maximizes her utility that depends on the product price, distance traveled to the store and reservation price, known to the retailer. The retailer's bilevel optimization problem is transformed into an integer optimization formulation. Small size instances are solved optimally, while for large instances, we explore Benders Decomposition, Branch and Cut and Cut and Branch to solve the problem. Our computational results show that the proposed Cut and Branch method obtains the best results, and improves on the current state of the art.

During this pandemic crisis, supply chain management (SCM) has emerged as a critical source of competitive advantage driving organizational performance, especially in the agri-food sector, since public health and consumers’ confidence as well as firms’ survival depend on the effectiveness of supply chain networks. This study adopts two central SCM practices, namely strategic suppliers’ partnerships and partners’ information quality & sharing and tests their relationships with competitive advantage (quality, process flexibility, and time to market) and business performance (profitability and market share), based on an empirical study of 300 enterprises in the agri-food sector in Greece. After data collection, we deploy a diagnostic-exploratory model, utilizing fuzzy cognitive mapping, with agent-based modeling following up for development for data prediction and simulation. Consequently, we found that supply chain firms’ compelling and robust relationships with supply chain partners ...

The COVID-19 pandemic exposed the vulnerability of the Canadian economy on many fronts. When the demand for lifesaving equipment increased globally, the supply chain networks were broken by the direct involvement of other countries. The rising competition and interruptions caused Canada to face significant difficulties in global markets to secure critical medical equipment and protective materials. Not only hospitals and healthcare workers but also the public and patients had no access to the needed equipment even though companies and organizations in the country have the required capacity and resources. In such emergency times, Canada should produce the essential equipment within the country. We propose a four-step strategic product manufacturing system to ensure crisis response. The first and second steps are creating a manufacturing capability database of Canadian companies and a library of product families, respectively. These two steps should be completed before the crisis. The third step involves emergency need analysis, equipment design and forecasting. Finally, the fourth step is developing a virtual supply chain network platform through which the procurement, production, and transportation activities will be scheduled based on the capability database, product families library, and requirements analysis in the most efficient and economical way possible. The research utilizes various tools such as forecasting, optimization, simulation, multi-criteria decision making, and engineering design tools.

The study was carried out on the impact of critical thinking on effective implementation of strategy in the Nigerian Economy (A study of Zenith bank plc). The primary objective of the study was to establish the importance of strategic thinking skills for business competitiveness. To achieve this objective, four research questions and two research hypotheses were formulated to guide the study. The research was design as an in-depth case study and the primary data were collected with the help of a well-structured questionnaires of two sections administered to Zenith Bank plc, Lagos State. The collected data were analyzed with tables and simple percentages to analyze the research questions while Chi-square statistical tool was used to test research hypotheses. The major finding from the study shows that Critical thinking has been one of the tools used in our daily lives to deal with the challenges for survival. Therefore, the study recommends that Government and educational authorities should always provide enabling environments and materials for teaching critical thinking skills to students in universities and other levels of education.

The supply chain network design not only assists organizations production process (e.g.,plan, control and execute a product’s flow) but also ensure what is the growing need for companies in a longterm. This paper develops a three-echelon supply chain network problem including multiple plants, multiple distributors, and multiple retailers with amulti-mode demand satisfaction policy inside of production planning and maintenance. The problem is formulated as a mixed-integer linear programming model. Because of its NP-hardness, three meta-heuristic algorithms(i.e., tabu search, harmony search and genetic algorithm) are used to solve the given problem. Also, theTaguchi method is used to choose the best levels of the parameters of the proposedmeta-heuristic algorithms. The results show that HS has abetter solution quality than two other algorithms.

A supply chain (SC) is a coordinated system involved in moving products or services from supplier to customer. With growing focus on supply chain management, it is realized that inventories across the supply chain should be efficiently managed through greater cooperation and better coordination. Multi-agent systems (MAS) offer a new dimension for cooperation and coordination. MAS consist of a collection of automated agents who can perform a specific task intelligently without any human supervision and communicate with each other cooperatively. In this research, a multi-agent system has been developed to simulate a multi echelon SC. These agents are coordinated to control inventories and minimize the total cost of SC by sharing information, forecasting knowledge and using negotiation mechanism in special situation. The result showed that in comparison to a traditional supply chain network, this system decreases the total cost and bullwhip effect. Keywords Supply chain management • Inventory control • Multi-agent system • Negotiation mechanism 1 Introduction In an era of globalisation, in which key account management, products, and services designed and delivered around specific customer requirements, supply chains' mechanism distinguish between success and failure. The council of supply chain management professionals (CSCMP) defines supply chain management as follows: "Supply chain management encompasses the planning and management of all activities involved in sourcing and procurement, conversion, and all logistics management activities. Importantly, it also includes coordination and collaboration with channel partners, which can be suppliers, intermediaries, third-party service providers, and customers".

Traditional planning deals with the problem of finding activities to satisfy a given goal while traditional scheduling solves the problem of allocating known activities to limited resources and to limited time. In many real-life problems both tasks should be accomplished together. We give an example of such integrated planning and scheduling problem and in the software demonstration we show how the problem is solved by the Visopt ShopFloor system Keywords: applications of planning and scheduling, planning and scheduling with complex domain models, constraint reasoning for planning and scheduling

The objective of this paper is to find how far the Just-in-Time system is being implemented by Portuguese manufacturing firms, as well as assessing its perception and its potential benefits by managers. First, several studies about the implementation of the Just-in-Time system in various countries over the past 25 years are reviewed, and then the descriptive survey research is reported. Data were collected from a mail questionnaire sent to a few hundred firms in Portugal. The findings show that the surveyed firms view the Just-in-Time system as a way to reduce inventories, to increase quality, and to eliminate waste. Despite this good perception, less than 6% of the surveyed firms have the necessary conditions to successfully implement a Just-in-Time system. A significant practical implication of this study is that Portuguese firms should use Just-in-Time as a philosophy rather than as a solution for operations-related problems. Another contribution is to point out the most common d...

Scope and purpose-Human blood is a product of unique medical value. It is perishable, having a usable lifetime of 21 days, and its supply and demand are probabilistic. These factors make the efficient management of the regional blood resources a very complex task. This paper describes a prototype blood distribution system currently in effect in Long Island, New York. The system is based on a provedly efficient analytical model, and is completely computerized, as part of a larger blood management network. The system has been in operation for three years. It has introduced a routine operation in the management of the blood region, and has drastically reduced the outdating and shortage incidents in the region.

I will always be thankful and grateful to my academic advisor and dissertation chair, John F. Smith Memorial Professor Anna Nagurney, for her support, guidance, and patience during the five years of my doctoral studies. I would like to thank her especially for accepting me as her doctoral student which was one of the most rewarding experiences of my life. Under her guidance, I was able to achieve many milestones and grew intellectually and personally. I will especially remember her guidance and support for my first publication and my first conference attendance. Her dedication to her profession, her enthusiasm, energy, and attention to details have always motivated me to work hard and be better. As a future female academic, I see her as a great role model and a true leader. I feel extremely lucky to have Professor Nagurney as my advisor.

Various behavioral issues are at stake in the health care sector, for example, the current strong plea for more demand-based care provision as opposed to traditional supply-driven approaches. Healthcare organizations are increasingly in need of systems and approaches that allow them to be more responsive to the needs and desires of their clients. To cope with heterogeneous and multiple demands, the application of modularity is increasingly proposed in care and services. In this paper the purpose is to study how interpersonal behavior responsive to client needs and values can be accommodated in modular care provision. Drawing on relevant literature from various service-related disciplines, we develop insight into how customization and personalization are simultaneously practiced by means of case research in the context of long-term care for elder people. Our empirics indicate that in care for elder people, personalization complements customization in adapting supply to demand. Customization is used to better match the needs of an individual customer in terms of the content of the service. Personalization is also used for this purpose, however, by adapting the way in which the service is provided. Moreover, the practice of personalization effectuates customization over time. The paper shows the importance of human behavior in the application of modularity in long term care for elder people. Approaching the issue of adaptation through the lens of modularity offers care providers insight into how customization and personalization are related. These insights can be used for the design of care delivery systems that enable comprehensive adaptation of supply to heterogeneous customer demands over time.

The aim of this paper is to consider time-dependent variational and quasi-variational inequalities and to study under which assumptions the continuity of solutions with respect to the time can be ensured. Making on appropriate use of the set convergence in Mosco's sense, we get the desiderate continuity results for strongly monotone variational and quasi-variational inequalities. The continuity results allow us to provide a discretization procedure for the calculation of the solution to the variational inequality which expresses the time-dependent traffic network equilibrium problem.