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

Analysis of Decision Support Systems of Industrial Relevance: Application Potential of Fuzzy and Grey Set Theories

The present work articulates few case empirical studies on decision making in industrial context. Development of variety of Decision Support System (DSS) under uncertainty and vague information is attempted herein. The study emphases on five important decision making domains where effective decision making may surely enhance overall performance of the organization. The focused territories of this work are i) robot selection, ii) g-resilient supplier selection, iii) third party logistics (3PL) service provider selection, iv) assessment of supply chain’s g-resilient index and v) risk assessment in e-commerce exercises. Firstly, decision support systems in relation to robot selection are conceptualized through adaptation to fuzzy set theory in integration with TODIM and PROMETHEE approach, Grey set theory is also found useful in this regard; and is combined with TODIM approach to identify the best robot alternative. In this work, an attempt is also made to tackle subjective (qualitative) and objective (quantitative) evaluation information simultaneously, towards effective decision making. Supplier selection is a key strategic concern for the large-scale organizations. In view of this, a novel decision support framework is proposed to address g-resilient (green and resilient) supplier selection issues. Green capability of suppliers’ ensures the pollution free operation; while, resiliency deals with unexpected system disruptions. A comparative analysis of the results is also carried out by applying well-known decision making approaches like Fuzzy- TOPSIS and Fuzzy-VIKOR. In relation to 3PL service provider selection, this dissertation proposes a novel ‘Dominance- Based’ model in combination with grey set theory to deal with 3PL provider selection, considering linguistic preferences of the Decision-Makers (DMs). An empirical case study is articulated to demonstrate application potential of the proposed model. The results, obtained thereof, have been compared to that of grey-TOPSIS approach. Another part of this dissertation is to provide an integrated framework in order to assess gresilient (ecosilient) performance of the supply chain of a case automotive company. The overall g-resilient supply chain performance is determined by computing a unique ecosilient (g-resilient) index. The concepts of Fuzzy Performance Importance Index (FPII) along with Degree of Similarity (DOS) (obtained from fuzzy set theory) are applied to rank different gresilient criteria in accordance to their current status of performance. The study is further extended to analyze, and thereby, to mitigate various risk factors (risk sources) involved in e-commerce exercises. A total forty eight major e-commerce risks are recognized and evaluated in a decision making perspective by utilizing the knowledge acquired from the fuzzy set theory. Risk is evaluated as a product of two risk quantifying parameters viz. (i) Likelihood of occurrence and, (ii) Impact. Aforesaid two risk quantifying parameters are assessed in a subjective manner (linguistic human judgment), rather than exploring probabilistic approach of risk analysis. The ‘crisp risk extent’ corresponding to various risk factors are figured out through the proposed fuzzy risk analysis approach. The risk factor possessing high ‘crisp risk extent’ score is said be more critical for the current problem context (toward e-commerce success). Risks are now categorized into different levels of severity (adverse consequences) (i.e. negligible, minor, marginal, critical and catastrophic). Amongst forty eight risk sources, top five risk sources which are supposed to adversely affect the company’s e-commerce performance are recognized through such categorization. The overall risk extent is determined by aggregating individual risks (under ‘critical’ level of severity) using Fuzzy Inference System (FIS). Interpretive Structural Modeling (ISM) is then used to obtain structural relationship amongst aforementioned five risk sources. An appropriate action requirement plan is also suggested, to control and minimize risks associated with e-commerce exercises

Multiple-Criteria Decision Making

Decision-making on real-world problems, including individual process decisions, requires an appropriate and reliable decision support system. Fuzzy set theory, rough set theory, and neutrosophic set theory, which are MCDM techniques, are useful for modeling complex decision-making problems with imprecise, ambiguous, or vague data.This Special Issue, “Multiple Criteria Decision Making”, aims to incorporate recent developments in the area of the multi-criteria decision-making field. Topics include, but are not limited to:- MCDM optimization in engineering;- Environmental sustainability in engineering processes;- Multi-criteria production and logistics process planning;- New trends in multi-criteria evaluation of sustainable processes;- Multi-criteria decision making in strategic management based on sustainable criteria

Proceedings of the 2nd Conference on Production Systems and Logistics (CPSL 2021)

Proceedings of the CPSL 202

Green Technologies for Production Processes

This book focuses on original research works about Green Technologies for Production Processes, including discrete production processes and process production processes, from various aspects that tackle product, process, and system issues in production. The aim is to report the state-of-the-art on relevant research topics and highlight the barriers, challenges, and opportunities we are facing. This book includes 22 research papers and involves energy-saving and waste reduction in production processes, design and manufacturing of green products, low carbon manufacturing and remanufacturing, management and policy for sustainable production, technologies of mitigating CO2 emissions, and other green technologies

Design and Optimization of Closed-Loop Supply Chain Management

Because of cost and environmental concerns, reverse supply chain (RSC) has received a lot of attention. RSC is defined as the activities of the collection and recovery of product returns in supply chain management. The integration of forward supply chain (FSC) and RSC results in a closed-loop supply chain (CLSC). In this dissertation, FSC, RSC, and CLSC are introduced. Then, the research objectives are mentioned. The objective of this dissertation is to develop effective approaches to support closed-loop supply chain configurations and analyses, especially develop methodologies to examine impacts of multi-objectives, and uncertainty on CLSC. In Chapter 2, literature of CLSC configuration is reviewed including deterministic and uncertain models. In addition, gaps in the literature are mentioned. In Chapter 3, a facility location model is examined. After problem definition, a mixed-integer linear programming model is proposed. Then, the model is developed to consider multi-objectives under uncertain demand and return. In Chapter 4, a CLSC network is examined. In this chapter, an integrated model for CLSC configuration and supplier selection is proposed and a solution approach is developed for the multi-objective model. A numerical example is used to validate the model. In Chapter 5, a three stage model for closed-loop supply chain configuration is proposed based on a general network. It is supposed that demand is an uncertain parameter. Besides, an illustrative example is applied to show the three-stage model. In addition, managerial insights are discussed in this chapter. In Chapter 6, a mixed-integer linear programming model is proposed to configure a CLSC network. The network has been designed based on product life cycle. The objective is to maximize profit by determining quantity of parts and products in the network. We also extend the model for the condition that the remanufactured products are sent to the secondary market. Finally in Chapter 7, conclusions and future works are provided

An investigation into Supplier Selections and Contingency Freight Consolidation for Less-Than-Truckload Logisitics

This study deals with the supplier selection problem in which truck com panies are considered as supplier for the transportation service and freight consolidation scheduling problems for Third Party Logistic (3PL) companies. We present two novel investigations for the supplier selection problem. In the first one, we make some analyses on the commonly used methods for supplier selection problems which are the Multi-Criteria Decision Making (MCDM) methods, namely Analytic Hierarchy Process (AHP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and VIekriter ijumsko KOmpromisno Rangiranje (VIKOR). Then we evaluate the results of each method based on the other two methods and conduct some tests for relying on a single method by the regret based measure approaches that we developed. In this way, we offer two effective approaches for combining the results of the individual MCDM approaches. Note that we do not propose an integration of the approaches, but a combination of the results of different MCDM methods in a systematic way instead of relying on a result of an indi vidual method. In the second study of supplier selection, we handle the issue of missing expert knowledge. When data is not available, researchers rely on expert knowledge. Therefore, there is a tendency to use MCDM methods for supplier selection problem due to working ability of MCDM methods with expert knowledge. However, experts do not always have full knowledge of all evaluation criteria. We offer a reliable solution for this problem. We integrate MCDM methods and Bayesian Network (BN) in a novel way that they can compensate each others' limitations with their strengths. We mainly rank the alternative suppliers with TOPSIS which has two inputs: weights of the deci sion criteria and initial decision matrix. We obtain the weights of the criteria from AHP and elicit the initial decision matrix from BN. Causal graphical structure and parameterization of BN is done by Decision Making Trial and Evaluation Laboratory (DEMATEL). Here, experts submit their knowledge about the decision criteria linguistically. Ranked Nodes tool of BN provides the experts to submit their knowledge with verbal expressions in an ordinal scale as low, medium, high. If the experts do not have full knowledge about some of the criteria BN estimates the missing value of criteria based on the available knowledge of the experts and causal relationship between the cri teria probabilistically. According to the obtained new knowledge(evidence) BN updates the values of the network and provides updated information to decision makers dynamically. Finally, we conducted sensitivity analyses for the value of knowledge followed by a case study. In the second part of this research, we investigate the freight consolidation scheduling problem. We address the problem in a particular way due to the preference of a 3PL company that operates in the UK. We consolidate the orders up to 3. First we investigate the possible consolidation configurations of orders as singleton(one), pair and triplets. We compute all the savings obtained by consolidation among non-consolidation case. Then we use these configurations and their saving values as input in our exact approaches like the 0-1 Integer Linear Programming (ILP) and the set partitioning formula tion which we developed. We also presented some tightening constraints into the set partitioning formulation and tested them for different size of the data sets. On the other hand we also tackled the problem using metaheuristics to overcome the computational time for larger instances. We offered Variable Neighbourhood Search (VNS) algorithm using six neighbourhood structures and two local searches: one performs within the route and the other one performs between the routes. The proposed neighbourhood structures are compatible with the purpose of the improvement of the consolidated ship ment configurations up to three requests. On the other hand to perturb the solution and improve it with the repair mechanism we offered Large Neigh bourhood Search (LNS) algorithm. In LNS algorithm, one of the removal operators performs effectively in a guided way by destroying the consolida tion configurations which have negative effect on savings. We also propose to hybridize the VNS/LNS algorithms. Lastly we discuss about the com putational results in terms of deviation from the optimal results and com putational time effectiveness. We finalize the study with a summary of the research, limitations and suggestions for further work. The thesis is made up of eight chapters. In the first chapter, the problem definition, a brief of the study and contributions are presented. In chapter 2, the literature review for supplier selection and order consolidation scheduling problems are given. Chapter 3 propose a deterministic rule for the combina tion of the results of different methods for supplier selection problem while Chapter 4 deals with the case of lack of complete expert knowledge for the supplier selection problem and proposes a novel MCDM-BN integration for this purpose. Chapter 5 discusses the order consolidation scheduling problem and defines all the possible configurations with their respective savings. In chapter 6, exact approaches for the order consolidation scheduling problem are provided, namely, a 0-1 ILP and a set partitioning formulation enhanced by valid inequalities. Chapter 7 treats the same scheduling problem by de signing and implementing two metaheuristics approaches, namely, variable neighbourhood search (VNS) and large neighbourhood search (LNS) as well as their hybridisation. Chapter 8 is the final chapter, it covers a summary of our findings and present limitations of the study and outlines suggestions as future work

MANAJEMEN RANTAI PASOK AGROINDUSTRI: Pendekatan Berkelanjutan untuk Pengukuran Kinerja dan Penilaian Risiko

Manajemen rantai pasok telah menjadi sebuah pendekatan yang andal dalam peningkatan daya saing bisnis termasuk agroindustri. Isu lingkungan dan sosial politik telah menjadi bagian penting dalam manajemen rantai pasok. Perkembangan selanjutnya adalah membangun manajemen rantai pasok yang mempertimbangkan aspek ekonomi dan non ekonomi yang dikenal dengan istilah manajemen rantai pasok berkelanjutan. Aspek non ekonomi yang dimaksudkan adalah aspek lingkungan dan sosial politik. Kedua aspek ini perlu dipertimbangkan selain aspek ekonomi karena kegiatan bisnis tidak dapat dilepaskan dari kepentingan masyarakat dan pemerintah.  Buku ini bermaksud untuk berkontribusi dalam pengayaan pemahaman manajemen rantai pasok berkelanjutan. Fokus dari isi buku ini adalah kinerja dan risiko. Kedua isu ini sangat menarik untuk dijelaskan dalam manajemen rantai pasok berkelanjutan karena berkelanjutan berkaitan dengan pencapaian operasi rantai pasok dan tantangan masa depan. Kinerja berkaitan dengan pencapaian target, sedangkan risiko berkaitan dengan ketidakpastian yang dihadapi operasi rantai pasok di masa datang. Kedua hal ini membutuhkan sebuah pendekatan yang handal dan tepat guna. Sistem penunjang keputusan dipilih sebagai alat yang berguna untuk menilai kinerja dan memprediksi risiko