Uncertain Multi-Criteria Optimization Problems

Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems

Decision support models for supplier development: Systematic literature review and research agenda

The continuing trend towards sourcing components and semi-finished goods for less vertically integrated manufacturing systems globally leads to a dramatic increase in supply options for companies. To ensure that companies benefit from the potentials global sourcing offers, supplier-buyer relationships need to be managed efficiently. Due to the decreasing share of value-adding activities provided in-house, suppliers are more and more considered as an essential contributor to the buying company's competitive position. Consequently, to realize and sustain competitive advantages, companies try to establish institutionalized long-term relationships to their most important suppliers and to actively improve the productivity and performance of their supplier base. To support supplier development in practice, researchers have developed decision support models that provide assistance in selecting and implementing suitable supplier development activities. The aim of this paper is to provide a comprehensive and systematic overview of decision support models for supplier development and to develop a research agenda that helps to identify promising areas for future research in this area. First, typical applications for supplier development as well as potential development measures that can be adopted to improve the performance of suppliers are identified. Secondly, a systematic literature review with a focus on decision support models for supplier development is conducted. Based on the analysis of the literature, we define a research agenda that synthesizes key trends and promising research opportunities and thus highlight areas where more decision support models are needed to foster supplier development initiatives in practice

A Review of the Criteria and Methods of Reverse Logistics Supplier Selection

This article presents a literature review on reverse logistics (RL) supplier selection in terms of criteria and methods. A systematic view of past work published between 2008 and 2020 on Web of Science (WOS) databases is provided by reviewing, categorizing, and analyzing relevant papers. Based on the analyses of 41 articles, we propose a three-stage typology of decision-making frameworks to understanding RL supplier selection, including (a) establishment of the selection criteria; (b) calculation of the relative weights and ranking of the selection criteria; (c) ranking of alternatives (suppliers). The main discoveries of this review are as follows. (1) Attention to the field of RL supplier selection is increasing, as evidenced by the increasing number of papers in the field. With the adaption of circular economy legislation and the need resource and business resilience, it is expected that RL and RL supplier selection will be a hot topic in the near future. (2) A large number of papers take “sustainability” as the theoretical approach to carry out research and use it as the basis for determining the criteria. (3) Multi-criteria decision making (MCDM) methods have been widely used in RL supplier selection and have been constantly innovated. (4) Artificial intelligence methods are also gradually being applied. Finally, gaps in the literature are identified to provide directions for future research. (5) Value-added service is underrepresented in the current study and needs further attention

Reprint of "Decision support models for supplier development: Systematic literature review and research agenda"

The continuing trend towards sourcing components and semi-finished goods for less vertically integrated manufacturing systems globally leads to a dramatic increase in supply options for companies. To ensure that companies benefit from the potentials global sourcing offers, supplier-buyer relationships need to be managed efficiently. Due to the decreasing share of value-adding activities provided in-house, suppliers are more and more considered as an essential contributor to the buying company's competitive position. Consequently, to realize and sustain competitive advantages, companies try to establish institutionalized long-term relationships to their most important suppliers and to actively improve the productivity and performance of their supplier base. To support supplier development in practice, researchers have developed decision support models that provide assistance in selecting and implementing suitable supplier development activities. The aim of this paper is to provide a comprehensive and systematic overview of decision support models for supplier development and to develop a research agenda that helps to identify promising areas for future research in this area. First, typical applications for supplier development as well as potential development measures that can be adopted to improve the performance of suppliers are identified. Secondly, a systematic literature review with a focus on decision support models for supplier development is conducted. Based on the analysis of the literature, we define a research agenda that synthesizes key trends and promising research opportunities and thus highlight areas where more decision support models are needed to foster supplier development initiatives in practice

Application of Optimization in Production, Logistics, Inventory, Supply Chain Management and Block Chain

The evolution of industrial development since the 18th century is now experiencing the fourth industrial revolution. The effect of the development has propagated into almost every sector of the industry. From inventory to the circular economy, the effectiveness of technology has been fruitful for industry. The recent trends in research, with new ideas and methodologies, are included in this book. Several new ideas and business strategies are developed in the area of the supply chain management, logistics, optimization, and forecasting for the improvement of the economy of the society and the environment. The proposed technologies and ideas are either novel or help modify several other new ideas. Different real life problems with different dimensions are discussed in the book so that readers may connect with the recent issues in society and industry. The collection of the articles provides a glimpse into the new research trends in technology, business, and the environment

Is foreign-bank efficiency in financial centers driven by home-country characteristics?

This paper investigates the effects of home country banking regulations on the performance of foreign banks in Luxembourg’s financial center. We control for the main regulatory indicators, such as capital requirements, private monitoring, official disciplinary power and restrictions on bank activities, accounting for the regulatory regime applied to foreign banks. We also control for the level of GDP in the home country and its position in the business cycle. The two-stage bootstrap method proposed by Simar and Wilson (2007) is applied to bank panel data covering 1999-2009. The analysis carries policy implications for bank regulators in both home and host countries and provides insight into the choice between establishing a branch or a subsidiary, when developing cross-border activities through financial centers.

An integrated model for green partner selection and supply chain construction

Stricter governmental regulations and rising public awareness of environmental issues are pressurising firms to make their supply chains greener. Partner selection is a critical activity in constructing a green supply chain because the environmental performance of the whole supply chain is significantly affected by all its constituents. The paper presents a model for green partner selection and supply chain construction by combining analytic network process (ANP) and multi-objective programming (MOP) methodologies. The model offers a new way of solving the green partner selection and supply chain construction problem both effectively and efficiently as it enables decision-makers to simultaneously minimize the negative environmental impact of the supply chain whilst maximizing its business performance. The paper also develops an additional decision-making tool in the form of the environmental difference, the business difference and the eco-efficiency ratio which quantify the trade-offs between environmental and business performance. The applicability and practicability of the model is demonstrated in an illustration of its use in the Chinese electrical appliance and equipment manufacturing industry

Efficiency Analysis of German Electricity Distribution Utilities : Non-Parametric and Parametric Tests

This paper applies parametric and non-parametric and parametric tests to assess the efficiency of electricity distribution companies in Germany. We address traditional issues in electricity sector benchmarking, such as the role of scale effects and optimal utility size, as well as new evidence specific to the situation in Germany This paper applies parametric and non-parametric and parametric tests to asses the efficiency of electricity distribution companies in Germany. We use labor, capital, and peak load capacity as inputs, and units sold and the number of customers as output. The data covers 307 (out of 553) German electricity distribution utilities. We apply a data envelopment analysis (DEA) with constant returns to scale (CRS) as the main productivity analysis technique, whereas stochastic frontier analysis (SFA) with distance function is our verification method. The results suggest that returns to scale play a minor role; only very small utilities have a significant cost advantage. Low customer density is found to affect the efficiency score significantly in the lower third of all observations. Surprisingly, East German utilities feature a higher average efficiency than their West German counterparts. The correlation tests imply a high coherence of the results. --Efficiency analysis,econometric methods,electricity distribution,benchmarking,Germany

Regulation and efficiency incentives: evidence from the England and Wales water and sewerage industry

This paper evaluates the impact of the tightening in price cap by OFWAT and of other operational factors on the efficiency of water and sewerage companies in England and Wales using a mixture of data envelopment analysis and stochastic frontier analysis. Previous empirical results suggest that the regulatory system introduced at privatization was lax. The 1999 price review signaled a tightening in regulation which is shown to have led to a significant reduction in technical inefficiency. The new economic environment set by price-cap regulation acted to bring inputs closer to their cost-minimizing levels from both a technical and allocative perspective

Sustainable supply chain network design integrating logistics outsourcing decisions in the context of uncertainties

Les fournisseurs de services logistiques (3PLs) possèdent des potentialités pour activer les pratiques de développement durables entre les différents partenaires d’une chaîne logistique (Supply Chain SC). Il existe un niveau optimal d'intégration des 3PLs en tant que fournisseurs, pour s’attendre à des performances opérationnelles élevées au sein de toute la SC. Ce niveau se traduit par la distinction des activités logistiques à externaliser de celles à effectuer en interne. Une fois que les activités logistiques externalisés sont stratégiquement identifiées, et tactiquement dimensionnées, elles doivent être effectuées par des 3PLs appropriés afin d’endurer les performances économiques ; sociales ; et environnementales de la SC. La présente thèse développe une approche holistique pour concevoir une SC durable intégrant les 3PLs, dans un contexte incertain d’affaires et politique de carbone. Premièrement, une approche de modélisation stochastique en deux étapes est suggérée pour optimiser à la fois le niveau d'intégration des 3PLs, et le niveau d'investissement en technologies sobres au carbone, et ce dans le contexte d’une SC résiliente aux changements climatiques. Notre SC est structurée de façon à capturer trois principales préoccupations du Supply Chain Management d’une entreprise focale FC (e. g. le fabricant) : Sécurité d’approvisionnement, Segmentation de distribution, et Responsabilité élargie des producteurs. La première étape de l'approche de modélisation suggère un plan stochastique basé sur des scenarios plus probables, afin de capturer les incertitudes inhérentes à tout environnement d’affaires (e. g. la fluctuation de la demande des différents produits ; la qualité et la quantité de retour des produits déjà utilisés ; et l’évolution des différents coûts logistiques en fonction du temps). Puis, elle propose un modèle de programmation stochastique bi-objectif, multi-période, et multi-produit. Le modèle de programmation quadratique, et non linéaire consiste à minimiser simultanément le coût logistique total espéré, et les émissions de Gaz à effet de Serre de la SC fermée. L'exécution du modèle au moyen d'un algorithme basé sur la méthode Epsilon-contraint conduit à un ensemble de configurations Pareto optimales d’une SC dé- carbonisée, avant tout investissement en technologie sobre au carbone. Chacune de ces configurations sépare les activités logistiques à externaliser de celles à effectuer en interne. La deuxième étape de l'approche de modélisation permet aux décideurs de choisir la meilleure configuration de la SC parmi les configurations Pareto optimales identifiées. Le concept de Prix du Carbone Interne est utilisé pour établir un plan stochastique du prix de carbone, dans le cadre d'un régime de déclaration volontaire du carbone. Nous proposons un ensemble des technologies sobres au carbone, dans le domaine de transport des marchandises, disposées à concourir pour contrer les politiques incertaines de carbone. Un modèle stochastique combinatoire, et linéaire est développé pour minimiser le coût total espéré, sous contraintes de l’abattement du carbone; limitation du budget, et la priorité attribuée pour chaque Technologie Réductrice de carbone (Low Carbone Reduction LCR). L'injection de chaque solution Pareto dans le modèle, et la résolution du modèle conduisent à sélectionner la configuration de la SC, la plus résiliente aux changements climatiques. Cette configuration définit non seulement le plan d'investissement optimal en LCR, mais aussi le niveau optimal d’externalisation de la logistique dans la SC. Deuxièmement, une fois que les activités logistiques à externaliser sont stratégiquement définies et tactiquement dimensionnées, elles ont besoin d’être effectuées par des 3PL appropriées, afin de soutenir la FC à construire une SC durable et résiliente. Nous suggérons DEA-QFD / Fuzzy AHP- Conception robuste de Taguchi : Une approche intégrée & robuste, pour sélectionner les 3PL candidats les plus efficients. Les critères durables et les risques liés à l’environnement d’affaires, sont identifiés, classés et ordonnés. Le Déploiement de la Fonction Qualité (QFD) est renforcé par le Processus Hiérarchique Analytique (AHP), et par la logique floue pour déterminer avec consistance l'importance relative de chaque facteur de décision, et ce, conformément aux besoins logistiques réels, et stratégies d'affaires de la FC. L’Analyse d’Enveloppement des Données (DEA) Data Envelopment Analysis conduit à limiter la liste des candidats, uniquement à ceux d’efficiences comparables, et donc excluant tout candidat moins efficient. La technique de conception robuste Taguchi permet de réaliser un plan d'expérience qui détermine un candidat idéal nommé 'optimum de Taguchi' ; un Benchmark pour comparer les 3PLs candidats. Par suite, le 3PL le plus efficient est celui le plus proche de cet optimum. Nous conduisons actuellement une étude de cas d’une entreprise qui fabrique et commercialise les fours à micro-ondes pour valider la modélisation stochastique en deux étapes. Certains aspects concernant l’application de l’approche sont reportés. Enfin, un exemple de sélection d’un 3PL durable pour s’occuper de la logistique inverse est fourni, pour démontrer l'applicabilité de l'approche intégrée & robuste, et montrer sa puissance par rapport aux approches populaires de sélection.The Third-Party Logistics service providers (3PLs) have the potentialities to activate sustainable practices between different partners of a Supply Chain (SC). There exists an optimal level of integrating 3PLs as suppliers of a Focal Company within the SC, to expect for high operational performances. This level leads to distinguish all the logistics activities to outsource from those to perform in-house. Once the outsourced logistics activities are strategically identified, and tactically dimensioned, they need to be performed by appropriate 3PLs to sustain economic, social and environmental performances of the SC. The present thesis develops a holistic approach to design a sustainable supply chain integrating 3PLs, in the context of business and carbon policy uncertainties. First, a two-stage stochastic modelling approach is suggested to optimize both the level of 3PL integration, and of Low Carbon Reduction LCR investment within a climate change resilient SC. Our SC is structured to capture three main SC management issues of the Focal Company FC (e.g. The manufacturer) : Security of Supplies; Distribution Segmentation; and Extended Producer Responsibility. The first-stage of the modelling approach suggests a stochastic plan based scenarios capturing business uncertainties, and proposes a two-objective, multi-period, and multi-product programming model, for minimizing simultaneously, the expected logistics total cost, and the Green House Gas GHG emissions of the whole SC. The run of the model by means of a suggested Epsilon-constraint algorithm leads to a set of Pareto optimal decarbonized SC configurations, before any LCR investment. Each one of these configurations distinguishes the logistics activities to be outsourced, from those to be performed in-house. The second-stage of the modelling approach helps the decision makers to select the best Pareto optimal SC configuration. The concept of internal carbon price is used to establish a stochastic plan of carbon price in the context of a voluntary carbon disclosure regime, and we propose a set of LCR technologies in the freight transportation domain ready to compete for counteracting the uncertain carbon policies. A combinatory model is developed to minimize the total expected cost, under the constraints of; carbon abatement, budget limitation, and LCR investment priorities. The injection of each Pareto optimal solution in the model, and the resolution lead to select the most efficient climate resilient SC configuration, which defines not only the optimal plan of LCR investment, but the optimal level of logistics outsourcing within the SC as well. Secondly, once the outsourced logistics are strategically defined they need to be performed by appropriate 3PLs for supporting the FC to build a Sustainable SC. We suggest the DEA-QFD/Fuzzy AHP-Taguchi Robust Design: a robust integrated selection approach to select the most efficient 3PL candidates. Sustainable criteria, and risks related to business environment are identified, categorized, and ordered. Quality Function Deployment (QFD) is reinforced by Analytic Hierarchic Process (AHP), and Fuzzy logic, to consistently determine the relative importance of each decision factor according to the real logistics needs, and business strategies of the FC. Data Envelopment Analysis leads to shorten the list of candidates to only those of comparative efficiencies. The Taguchi Robust Design technique allows to perform a plan of experiment, for determining an ideal candidate named ‘optimum of Taguchi’. This benchmark is used to compare the remainder 3Pls candidates, and the most efficient 3PL is the closest one to this optimum.We are currently conducting a case study of a company that manufactures and markets microwave ovens for validating the two-stage stochastic approach, and certain aspects of its implementation are provided. Finally, an example of selecting a sustainable 3PL, to handle reverse logistics is given for demonstrating the applicability of the integrated & robust approach, and showing its power compared to popular selection approaches. Keywords:Third Party Logistics; Green Supply Chain design; Stochastic Multi-Objective Optimization; Carbon Pricing; Taguchi Robust Design