Decision support system for vendor managed inventory supply chain:a case study

Vendor-managed inventory (VMI) is a widely used collaborative inventory management policy in which manufacturers manages the inventory of retailers and takes responsibility for making decisions related to the timing and extent of inventory replenishment. VMI partnerships help organisations to reduce demand variability, inventory holding and distribution costs. This study provides empirical evidence that significant economic benefits can be achieved with the use of a genetic algorithm (GA)-based decision support system (DSS) in a VMI supply chain. A two-stage serial supply chain in which retailers and their supplier are operating VMI in an uncertain demand environment is studied. Performance was measured in terms of cost, profit, stockouts and service levels. The results generated from GA-based model were compared to traditional alternatives. The study found that the GA-based approach outperformed traditional methods and its use can be economically justified in small- and medium-sized enterprises (SMEs)

An Investigation into Factors Affecting the Chilled Food Industry

With the advent of Industry 4.0, many new approaches towards process monitoring, benchmarking and traceability are becoming available, and these techniques have the potential to radically transform the agri-food sector. In particular, the chilled food supply chain (CFSC) contains a number of unique challenges by virtue of it being thought of as a temperature controlled supply chain. Therefore, once the key issues affecting the CFSC have been identified, algorithms can be proposed, which would allow realistic thresholds to be established for managing these problems on the micro, meso and macro scales. Hence, a study is required into factors affecting the CFSC within the scope of Industry 4.0. The study itself has been broken down into four main topics: identifying the key issues within the CFSC; implementing a philosophy of continuous improvement within the CFSC; identifying uncertainty within the CFSC; improving and measuring the performance of the supply chain. However, as a consequence of this study two further topics were added: a discussion of some of the issues surrounding information sharing between retailers and suppliers; some of the wider issues affecting food losses and wastage (FLW) on the micro, meso and macro scales. A hybrid algorithm is developed, which incorporates the analytic hierarchical process (AHP) for qualitative issues and data envelopment analysis (DEA) for quantitative issues. The hybrid algorithm itself is a development of the internal auditing algorithm proposed by Sueyoshi et al (2009), which in turn was developed following corporate scandals such as Tyco, Enron, and WorldCom, which have led to a decline in public trust. However, the advantage of the proposed solution is that all of the key issues within the CFSC identified can be managed from a single computer terminal, whilst the risk of food contamination such as the 2013 horsemeat scandal can be avoided via improved traceability

Economic and social satisfaction: The antecedents and consequence, and the moderating effect of brand strength in the context of retailer-manufacturer relationship in Yemen

Available literatures have confirmed that there is a complex relationship between food manufacturers and large retailers especially in the growing strength of retail organizations in both the Yemeni and global contexts. To empirically investigate this relationship, the present study employed one single model of manufacturer-retailer relationship based on a review of the literature: (1) the impact of marketing relationship bonds on retailer‟s economic and social satisfaction; (2) the relationship between economic and social satisfaction, and their affect on commitment; and (3) the moderating effect of the manufacturer brands‟ strength on the relationships between retailer‟s economic and social satisfaction, and retailers‟ commitment. This quantitative study presents and discusses empirical findings from a survey of 140 independent large retailers using partial least squares-structural equation modeling (PLS-SEM). The findings of the study largely supported the hypothesized relationships proposed in the theoretical model. The results revealed that organizational bonds, but not interpersonal bonds, were crucial in affecting retailer‟s economic satisfaction. Meanwhile, interpersonal bonds were crucial in affecting retailer‟s social satisfaction. The results also provided strong evidence of the relationship between retailer‟s economic and social satisfaction, which in turn are necessary determinants of retailer‟s commitment. The study also found that the strength of manufacturer‟s brands enhanced the relationship between economic satisfaction and commitment, but not the relationship between social satisfaction and commitment. This study offers several implications on how managers of national food manufacturers can ensure the long-term success of their mutual business relationship with large retailers in light of the growing power of retailers. Additionally, this study suggests further research to compare the levels of large retailer‟s economic and social satisfaction with national and foreign suppliers, and investigate relational bonds in order to develop and maintain the national manufacturer‟s relationships with their marketing channels to achieve competitive advantage

Supply Chain

Traditionally supply chain management has meant factories, assembly lines, warehouses, transportation vehicles, and time sheets. Modern supply chain management is a highly complex, multidimensional problem set with virtually endless number of variables for optimization. An Internet enabled supply chain may have just-in-time delivery, precise inventory visibility, and up-to-the-minute distribution-tracking capabilities. Technology advances have enabled supply chains to become strategic weapons that can help avoid disasters, lower costs, and make money. From internal enterprise processes to external business transactions with suppliers, transporters, channels and end-users marks the wide range of challenges researchers have to handle. The aim of this book is at revealing and illustrating this diversity in terms of scientific and theoretical fundamentals, prevailing concepts as well as current practical applications

Collaborative Models for Supply Networks Coordination and Healthcare Consolidation

This work discusses the collaboration framework among different members of two complex systems: supply networks and consolidated healthcare systems. Although existing literature advocates the notion of strategic partnership/cooperation in both supply networks and healthcare systems, there is a dearth of studies quantitatively analyzing the scope of cooperation among the members and its benefit on the global performance. Hence, the first part of this dissertation discusses about two-echelon supply networks and studies the coordination of buyers and suppliers for multi-period procurement process. Viewing the issue from the same angel, the second part studies the coordination framework of hospitals for consolidated healthcare service delivery. Realizing the dynamic nature of information flow and the conflicting objectives of members in supply networks, a two-tier coordination mechanism among buyers and suppliers is modeled. The process begins with the intelligent matching of buyers and suppliers based on the similarity of users profiles. Then, a coordination mechanism for long-term agreements among buyers and suppliers is proposed. The proposed mechanism introduces the importance of strategic buyers for suppliers in modeling and decision making process. To enhance the network utilization, we examine a further collaboration among suppliers where cooperation incurs both cost and benefit. Coalitional game theory is utilized to model suppliers\u27 coalition formation. The efficiency of the proposed approaches is evaluated through simulation studies. We then revisit the common issue, the co-existence of partnership and conflict objectives of members, for consolidated healthcare systems and study the coordination of hospitals such that there is a central referral system to facilitate patients transfer. We consider three main players including physicians, hospitals managers, and the referral system. As a consequence, the interaction within these players will shape the coordinating scheme to improve the overall system performance. To come up with the incentive scheme for physicians and aligning hospitals activities, we define a multi-objective mathematical model and obtain optimal transfer pattern. Using optimal solutions as a baseline, a cooperative game between physicians and the central referral system is defined to coordinate decisions toward system optimality. The efficiency of the proposed approach is examined via a case study

Optimal Inventory Control and Distribution Network Design of Multi-Echelon Supply Chains

Optimale Bestandskontrolle und Gestaltung von Vertriebsnetzen mehrstufiger Supply Chains Aufgrund von Global Sourcing, Outsourcing der Produktion und Versorgung weltweiter Kunden innerhalb eines komplexen Vertriebsnetzes, in welchem mehrere Anlagen durch verschiedene Aktivitäten miteinander vernetzt sind, haben die meisten Unternehmen heutzutage immer komplexere Supply Chain-Netzwerke in einer immer unbeständiger werdenden Geschäftsumgebung. Mehr beteiligte Unternehmen in der Wertschöpfungskette bedeuten mehr Knoten und Verbindungen im Netzwerk. Folglich bringt die Globalisierung Komplexität und neue Herausforderungen, obwohl Unternehmen immer stärker von globalen Supply Chains profitieren. In einer solchen Geschäftsumgebung müssen sich die Akteure innerhalb der Supply Chain (SC) auf die effiziente Verwaltung und Koordination des Materialflusses im mehrstufigen System fokussieren, um diesen Herausforderungen handhaben zu können. In vielen Fällen beinhaltet die Supply Chain eines Unternehmens unterschiedliche Entscheidungen auf verschiedenen Planungsebenen, wie der Anlagenstandort, die Bestände und die Verkehrsmittel. Jede dieser Entscheidungen spielt eine bedeutende Rolle hinsichtlich der Gesamtleistung und das Verhältnis zwischen ihnen kann nicht ignoriert werden. Allerdings wurden diese Entscheidungen meist einzeln untersucht. In den letzten Jahren haben zahlreiche Studien die Bedeutung der Integration von beteiligten Entscheidungen in Supply Chains hervorgehoben. In diesem Zusammenhang sollten Entscheidungen über Anlagenstandort, Bestand und Verkehrsmittel gemeinsam in einem Optimierungsproblem des Vertriebsnetzes betrachtet werden, um genauere Ergebnisse für das Gesamtsystem zu erzeugen. Darüber hinaus ist ein effektives Management des Materialflusses über die gesamte Lieferkette hinweg, aufgrund der dynamischen Umgebung mit mehreren Zielen, ein schwieriges Problem. Die Lösungsansätze, die in der Vergangenheit verwendet wurden, um Probleme mehrstufiger Supply Chains zu lösen, basierten auf herkömmlichen Verfahren unter der Verwendung von analytischen Techniken. Diese sind jedoch nicht ausreichend, um die Dynamiken in Lieferketten zu bewältigen, aufgrund ihrer Unfähigkeit, mit den komplexen Interaktionen zwischen den Akteuren der Supply Chain umzugehen und das stochastische Verhalten zu repräsentieren, das in vielen Problemen der realen Welt besteht. Die Simulationsmodellierung ist in letzter Zeit zu einem wichtigen Instrument geworden, da ein analytisches Modell nicht in der Lage ist, ein System abzubilden, das sowohl der Variabilität als auch der Komplexität unterliegt. Allerdings erfordern Simulationen umfangreiche Laufzeiten, um möglichst viele Lösungen zu bewerten und die optimale Lösung für ein definiertes Problem zu finden. Um mit dieser Schwierigkeit umzugehen, muss das Simulationsmodell in Optimierungsalgorithmen integriert werden. In Erwiderung auf die oben genannten Herausforderungen, ist eines der Hauptziele dieser Arbeit, ein Modell und ein Lösungsverfahren für die optimale Gestaltung von Vertriebsnetzwerken integrierter Supply Chains vorzuschlagen, das die Beziehung zwischen den Entscheidungen der verschiedenen Planungsebenen berücksichtigt. Die Problemstellung wird mithilfe von Zielfunktionen formuliert, um die Kundenabdeckung zu maximieren, den maximalen Abstand von den Anlagenstandorten zu den Bedarfspunkten zu minimieren oder die Gesamtkosten zu minimieren. Um die optimale Anzahl, Kapazität und Lage der Anlagen zu bestimmen, kommen der Nondominated Sorting Genetic Algorithm II (NSGA-II) und der Quantum-based Particle Swarm Optimization Algorithm (QPSO) zum Einsatz, um dieses Optimierungsproblem im Spannungsfeld verschiedener Ziele zu lösen. Aufgrund der Komplexität mehrstufiger Systeme und der zugrunde liegenden Unsicherheiten, wurde die Optimierung von Beständen über die gesamte Lieferkette hinweg zur wesentlichen Herausforderung, um die Kosten zu reduzieren und die Serviceanforderungen zu erfüllen. In diesem Zusammenhang ist das andere Ziel dieser Arbeit die Darstellung eines simulationsbasierten Optimierungs-Frameworks, in dem die Simulation, basierend auf der objektorientierten Programmierung, entwickelt wird und die Optimierung metaheuristische Techniken mit unterschiedlichen Kriterien, wie NSGA-II und MOPOSO, verwendet. Insbesondere das geplante Framework regt einen großen Nutzen an, sowohl für das Bestandsoptimierungsproblem in mehrstufigen Supply Chains, als auch für andere Logistikprobleme.Today, most companies have more complex supply chain networks in a more volatile business environment due to global sourcing, outsourcing of production and serving customers all over the world with a complex distribution network that has several facilities linked by various activities. More companies involved within the value chain, means more nodes and links in the network. Therefore, globalization brings complexities and new challenges as enterprises increasingly benefit from global supply chains. In such a business environment, Supply Chain (SC) members must focus on the efficient management and coordination of material flow in the multi-echelon system to handle with these challenges. In many cases, the supply chain of a company includes various decisions at different planning levels, such as facility location, inventory and transportation. Each of these decisions plays a significant role in the overall performance and the relationship between them cannot be ignored. However, these decisions have been mostly studied individually. In recent years, numerous studies have emphasized the importance of integrating the decisions involved in supply chains. In this context, facility location, inventory and transportation decisions should be jointly considered in an optimization problem of distribution network design to produce more accurate results for the whole system. Furthermore, effective management of material flow across a supply chain is a difficult problem due to the dynamic environment with multiple objectives. In the past, the majority of the solution approaches used to solve multi-echelon supply chain problems were based on conventional methods using analytical techniques. However, they are insufficient to cope with the SC dynamics because of the inability to handle to the complex interactions between the SC members and to represent stochastic behaviors existing in many real world problems. Simulation modeling has recently become a major tool since an analytical model is unable to formulate a system that is subject to both variability and complexity. However, simulations require extensive runtime to evaluate many feasible solutions and to find the optimal one for a defined problem. To deal with this problem, simulation model needs to be integrated in optimization algorithms. In response to the aforementioned challenges, one of the primary objectives of this thesis is to propose a model and solution method for the optimal distribution network design of an integrated supply chain that takes into account the relationship between decisions at the different levels of planning horizon. The problem is formulated with objective functions to maximize the customer coverage or minimize the maximal distance from the facilities to the demand points and minimize the total cost. In order to find optimal number, capacity and location of facilities, the Nondominated Sorting Genetic Algorithm II (NSGA-II) and Quantum-based Particle Swarm Optimization Algorithm (QPSO) are employed for solving this multiobjective optimization problem. Due to the complexities of multi-echelon system and the underlying uncertainty, optimizing inventories across the supply chain has become other major challenge to reduce the cost and to meet service requirements. In this context, the other aim of this thesis is to present a simulation-based optimization framework, in which the simulation is developed based on the object-oriented programming and the optimization utilizes multi-objective metaheuristic techniques, such as the well-known NSGA-II and MOPSO. In particular, the proposed framework suggests a great utility for the inventory optimization problem in multi-echelon supply chains, as well as for other logistics-related problems

Decision Support System for Managing Reverse Supply Chain

Reverse logistics are becoming more and more important in the overall Industry area because of the environment and business factors. Planning and implementing a suitable reverse logistics network could bring more profit, customer satisfaction, and an excellent social picture for companies. But, most of the logistics networks are not equipped to handle the return products in reverse channels. Reverse logistics processes and plans rely heavily on reversing the supply chain so that companies can correctly identify and categorize returned products for disposition, an area that offers many opportunities for additional revenue. The science of reverse logistics includes return policy administration, product recall protocols, repairs processing, product repackaging, parts management, recycling, product disposition management, maximizing liquidation values and much more. The focus of this project is to develop a reverse logistics management system/ tools (RLMS). The proposed tools are demonstrated in the following order. First, we identify the risks involved in the reverse supply chain. Survey tool is used to collect data and information required for analysis. The methodologies that are used to identify key risks are the six sigma tools, namely Define, Measure, Analyse, Improve and Control (DMAIC), SWOT analysis, cause and effect, and Risk Mapping. An improved decision-making method using fuzzy set theory for converting linguistic data into numeric risk ratings has been attempted. In this study, the concept of ‘Left and Right dominance approach’(Chen and Liu, 2001) and Method of ‘In center of centroids’ (Thoran et al., 2012a,b) for generalized trapezoidal fuzzy numbers has been used to quantify the ‘degree of risk’ in terms of crisp ratings. After the analysis, the key risks are identified are categorized, and an action requirement plan suggested for providing guidelines for the managers to manage the risk successfully in the context of reverse logistics. Next, from risk assessment findings, information technology risk presents the highest risk impact on the performance of the reverse logistics, especially lack of use of a decision support system (DSS). We propose a novel multi-attribute decision (MADM) support tool that can categorizes return products and make the best alternative selection of recovery and disposal option using carefully considered criteria using MADM decision making methodologies such as fuzzy MOORA and VIKOR. The project can be applied to all types of industries. Once the returned products are collected and categorized at the retailers/ Points of return (PoR), an optimized network is required to determine the number of reprocessing centres to be opened and the optimized optimum material flow between retailers, reprocessing, recycling and disposal centers at minimum costs. The research develops a mixed integer linear programming model for two scenarios, namely considering direct shipping from retailer/ PoR to the respective reprocessing centers and considering the use of centralized return centers (CRC). The models are solved using LINGO 15 software and excel solver tools respectively. The advantage of the implementation of our solution is that it will help improve performance and reduce time. This benefits the company by having a reduction in their cost due to uncertainties and also contributes to better customer satisfaction. Implementation of these tools at ABZ computer distributing company demonstrates how the reverse logistics management tools can used in order to be beneficial to the organization. The tool is designed to be easily implemented at minimal cost and serves as a valuable tool for personnel faced with significant and costly decisions regarding risk assessment, decision making and network optimization in the reverse supply chain practices

From Network to Web dimension in supply chain management

Cette thèse soutient que la dimension réseau, étant actuellement la portée du domaine de la gestion de chaîne logistique, contraint l’avancement de ce domaine et restreint des innovations conceptuelles et fondamentales capables d’adresser les grands défis économiques, environnementaux et sociaux. Les concepts de chaîne et de réseau ne reflètent pas la complexité des flux physiques, informationnels et financiers générés par les interactions qui ont lieu dans des réseaux interconnectés. Ces concepts n’offrent pas les fondations théoriques pour supporter des interventions allant au-delà d’un seul réseau et laissent échapper des opportunités nécessitant une vision multi-réseau. Ainsi, la dimension “web”, celle des réseaux de réseaux, est proposée comme une extension de la dimension réseau. Cette extension peut être vue comme l’étape naturelle suivante dans la progression qui a commencé par le niveau de gestion des opérations internes, est passée au niveau de la chaîne logistique et se trouve actuellement au niveau du réseau logistique. Après l’investigation théorique des raisons et de la façon d’intégrer la dimension web dans le domaine de la gestion de la chaîne logistique, la thèse étudie des implications importantes de cette intégration sur la collaboration inter-organisationnelle et le processus de prise de décision dans des environnements de webs logistiques. Elle démontre, en exploitant l’exemple des réseaux interconnectés ouverts, des potentialités inimaginables sans une vision web. Une méthodologie de conception d’un modèle de simulation permettant l’évaluation et la comparaison des webs ouverts par rapport aux webs existants est proposée. Puisque l’aide à la décision est une composante importante de la gestion de la chaîne logistique, la thèse contribue à déterminer les besoins des gestionnaires et à identifier les lignes directrices de la conception des outils d’aide à la décision offrant le support adéquat pour faire face aux défis et à la complexité des webs logistiques. Ces lignes directrices ont été compilées dans un cadre de conception des logiciels d’aide à la décision supportant la dimension web. Ce cadre est exploité pour développer quatre applications logicielles offrant aux praticiens et aux chercheurs des outils nécessaires pour étudier, analyser et démêler la complexité des webs logistiques.This thesis argues that the network dimension as the current scope of supply chain management is confining the evolution of this field and restricting the conceptual and fundamental innovations required for addressing the major challenges imposed by the evolution of markets and the increased intricacies of business relationships. The concepts of chain and network are limitative when attempting to represent the complexity of physical, informational and financial flows resulting from the interactions occurring in overlapping networks. They lack the theoretical foundations necessary to explain and encompass initiatives that go beyond a single chain or network. They also lead to overlook substantial opportunities that require beyond a network vision. Therefore, the “web” dimension, as networks of networks, is proposed as an extension to the network dimension in supply chain management. This new scope is the natural next step in the progression from the internal operations management level to the supply chain level and then to the supply network level. After a theoretical investigation of why and how the web dimension should be integrated into the supply chain management field, the thesis studies and discusses important implications of this integration on inter-organisational collaboration and of the decision-making processes in the logistic web environments. It demonstrates through the example of open interconnected logistic webs some of the potentials that cannot be imagined without a web vision. A methodology for designing a simulation model to assess the impact of such open webs versus existing webs is proposed. Since decision support is a key element in supply chain management, the thesis contributes to determine the needs of supply chain managers and identify the important axes for designing decision support systems that provide adequate assistance in dealing with the challenges and complexity presented by logistic web environments. The identified elements result in the establishment of a foundation for designing software solutions required to handle the challenges revealed by the web dimension. This conceptual framework is applied to the prototyping of four applications that have the potential of providing practitioners and researchers with the appropriate understanding and necessary tools to deal with the complexity of logistics webs

Selection of return channels and recovery options for used products

Due to legal, economic and socio-environmental factors, reverse logistics practices and extended producer responsibility have developed into a necessity in many countries. The end results and expectations may differ, but the motivation remains the same. Two significant components in a reverse logistics system -product recovery options and return channels - are the focus of this thesis. The two main issues examined are allocation of the returned products to recovery options, and selection of the collection methods for product returns. The initial segment of this thesis involves the formulation of a linear programming model to determine the optimal allocation of returned products differing in quality to specific recovery options. This model paves the way for a study on the effects of flexibility on product recovery allocation. A computational example utilising experimental data was presented to demonstrate the viability of the proposed model. The results revealed that in comparison to a fixed match between product qualities and recovery options, the product recovery operation appeared to be more profitable with a flexible allocation. The second segment of this thesis addresses the methods employed for the initial collection of returned products. A mixed integer nonlinear programming model was developed to facilitate the selection of optimal collection methods for these products. This integrated model takes three different initial collection methods into consideration. The model is used to solve an illustrative example optimally. However, as the complexity of the issue renders this process ineffective in the face of larger problems, the Lagrangian relaxation method was proposed to generate feasible solutions within reasonable computational times. This method was put to the test and the results were found to be encouraging