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Author: Lixin Cui Publisher: Open Dissertation Press ISBN: 9781361312308 Category : Languages : en Pages :
Book Description
This dissertation, "Integrated Supplier Selection and Order Allocation Incorporating Customer Flexibility" by Lixin, Cui, 崔麗欣, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Supplier selection and order allocation are significant decisions for a manufacturer to ensure stable material flows in a highly competitive supply chain, in particular when customers are willing to accept products with less desirable product attributes. Hence, this study develops efficient methodologies to solve optimally the integrated supplier selection and order allocation problem incorporating customer flexibility for a manufacturer producing multiple products over a multi-period planning horizon. In this research, a new fuzzy multi-attribute approach is proposed to evaluate customer flexibility which is characterized through range and response. The approach calculates the product's general utility value. This value is used by a bi-variant function which is developed to determine the retail price for the product. A new mixed integer program model describing the behavior of the basic problem is firstly developed. This basic model is the first to jointly determine: 1) type and quantity of the product variants to be offered; 2) the suppliers to be selected and orders to be allocated; and 3) inventory levels of product variants and raw materials/components. The objective is to maximize the manufacturer's total profit subject to various operating constraints. This basic problem constitutes a very complex combinatorial optimization problem that is Nondeterministic Polynomial (NP)-hard. To tackle this challenge, two new optimization algorithms, i.e., an improved genetic approach called king GA (KGA) and an innovative hybrid algorithm called (CP-SA) _I which combines the techniques of constraint programming and simulated annealing are developed to locate optimal solutions. Extensive computational experiments demonstrate the effectiveness of these algorithms and also show clearly that (CP-SA) _I outperforms KGA in terms of both solution quality and computational cost. To examine the influence of subcontracting as one widespread practice in modern production management, this study also develops a modified mathematical model. It shares some similarity with the basic model but brings additional complexity by taking into consideration subcontractors for inter-mediate components and machine capacity. Since (CP-SA) _I outperforms KGA, it is employed and modified to solve the modified problem. Hence, this study presents a new hybrid algorithm called (CP-SA) _II, to locate optimal solutions. This study also establishes a new parallel (CP-SA) _II algorithm to enhance the performance of (CP-SA) _II. This parallel algorithm is implemented on a distributed computing platform based on the contemporary Graphic Processing Unit (GPU) using the Compute Unified Device Architecture (CUDA) programming model. Extensive numerical experiments conducted clearly demonstrate that the parallel (CP-SA) _II algorithm and its serial counterpart are efficient and robust optimization tools for formulating integrated supplier selection and order allocation decisions. Sensitivity analysis is employed to study the effects of the critical parameters on the performance of these algorithms. Finally, the convergence behavior of the proposed parallel (CP-SA) _II algorithm is studied theoretically. The results prove that the search process eventually converges to the global optimum if the overall best solution is maintained over time. DOI: 10.5353/th_b4786938 Subjects: Business log
Author: Lixin Cui Publisher: Open Dissertation Press ISBN: 9781361312308 Category : Languages : en Pages :
Book Description
This dissertation, "Integrated Supplier Selection and Order Allocation Incorporating Customer Flexibility" by Lixin, Cui, 崔麗欣, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Supplier selection and order allocation are significant decisions for a manufacturer to ensure stable material flows in a highly competitive supply chain, in particular when customers are willing to accept products with less desirable product attributes. Hence, this study develops efficient methodologies to solve optimally the integrated supplier selection and order allocation problem incorporating customer flexibility for a manufacturer producing multiple products over a multi-period planning horizon. In this research, a new fuzzy multi-attribute approach is proposed to evaluate customer flexibility which is characterized through range and response. The approach calculates the product's general utility value. This value is used by a bi-variant function which is developed to determine the retail price for the product. A new mixed integer program model describing the behavior of the basic problem is firstly developed. This basic model is the first to jointly determine: 1) type and quantity of the product variants to be offered; 2) the suppliers to be selected and orders to be allocated; and 3) inventory levels of product variants and raw materials/components. The objective is to maximize the manufacturer's total profit subject to various operating constraints. This basic problem constitutes a very complex combinatorial optimization problem that is Nondeterministic Polynomial (NP)-hard. To tackle this challenge, two new optimization algorithms, i.e., an improved genetic approach called king GA (KGA) and an innovative hybrid algorithm called (CP-SA) _I which combines the techniques of constraint programming and simulated annealing are developed to locate optimal solutions. Extensive computational experiments demonstrate the effectiveness of these algorithms and also show clearly that (CP-SA) _I outperforms KGA in terms of both solution quality and computational cost. To examine the influence of subcontracting as one widespread practice in modern production management, this study also develops a modified mathematical model. It shares some similarity with the basic model but brings additional complexity by taking into consideration subcontractors for inter-mediate components and machine capacity. Since (CP-SA) _I outperforms KGA, it is employed and modified to solve the modified problem. Hence, this study presents a new hybrid algorithm called (CP-SA) _II, to locate optimal solutions. This study also establishes a new parallel (CP-SA) _II algorithm to enhance the performance of (CP-SA) _II. This parallel algorithm is implemented on a distributed computing platform based on the contemporary Graphic Processing Unit (GPU) using the Compute Unified Device Architecture (CUDA) programming model. Extensive numerical experiments conducted clearly demonstrate that the parallel (CP-SA) _II algorithm and its serial counterpart are efficient and robust optimization tools for formulating integrated supplier selection and order allocation decisions. Sensitivity analysis is employed to study the effects of the critical parameters on the performance of these algorithms. Finally, the convergence behavior of the proposed parallel (CP-SA) _II algorithm is studied theoretically. The results prove that the search process eventually converges to the global optimum if the overall best solution is maintained over time. DOI: 10.5353/th_b4786938 Subjects: Business log
Author: Mariya A. Sodenkamp Publisher: Infinite Study ISBN: Category : Languages : en Pages : 16
Book Description
We propose a novel meta-approach to support collaborative multi-objective supplier selection and order allocation (SSOA) decisions by integrating multi-criteria decision analysis and linear programming (LP).
Author: National Research Council Publisher: National Academies Press ISBN: 0309173418 Category : Technology & Engineering Languages : en Pages : 162
Book Description
The managed flow of goods and information from raw material to final sale also known as a "supply chain" affects everythingâ€"from the U.S. gross domestic product to where you can buy your jeans. The nature of a company's supply chain has a significant effect on its success or failureâ€"as in the success of Dell Computer's make-to-order system and the failure of General Motor's vertical integration during the 1998 United Auto Workers strike. Supply Chain Integration looks at this crucial component of business at a time when product design, manufacture, and delivery are changing radically and globally. This book explores the benefits of continuously improving the relationship between the firm, its suppliers, and its customers to ensure the highest added value. This book identifies the state-of-the-art developments that contribute to the success of vertical tiers of suppliers and relates these developments to the capabilities that small and medium-sized manufacturers must have to be viable participants in this system. Strategies for attaining these capabilities through manufacturing extension centers and other technical assistance providers at the national, state, and local level are suggested. This book identifies action steps for small and medium-sized manufacturersâ€"the "seed corn" of business start-up and developmentâ€"to improve supply chain management. The book examines supply chain models from consultant firms, universities, manufacturers, and associations. Topics include the roles of suppliers and other supply chain participants, the rise of outsourcing, the importance of information management, the natural tension between buyer and seller, sources of assistance to small and medium-sized firms, and a host of other issues. Supply Chain Integration will be of interest to industry policymakers, economists, researchers, business leaders, and forward-thinking executives.
Author: Tadeusz Sawik Publisher: Springer ISBN: 3319588230 Category : Business & Economics Languages : en Pages : 364
Book Description
This book deals with stochastic combinatorial optimization problems in supply chain disruption management, with a particular focus on management of disrupted flows in customer-driven supply chains. The problems are modeled using a scenario based stochastic mixed integer programming to address risk-neutral, risk-averse and mean-risk decision-making in the presence of supply chain disruption risks. The book focuses on innovative, computationally efficient portfolio approaches to supply chain disruption management, e.g., selection of primary and recovery supply portfolios, demand portfolios, capacity portfolios, etc. Numerous computational examples throughout the book, modeled in part on real-world supply chain disruption management problems, illustrate the material presented and provide managerial insights. In the computational examples, the proposed mathematical programming models are solved using an advanced algebraic modeling language such as AMPL and CPLEX, GUROBI and XPRESS solvers. The knowledge and tools provided in the book allow the reader to model and solve supply chain disruption management problems using commercially available software for mixed integer programming. Using the end-of chapter problems and exercises, the monograph can also be used as a textbook for an advanced course in supply chain risk management. After an introductory chapter, the book is then divided into five main parts. Part I addresses selection of a supply portfolio; Part II considers integrated selection of supply portfolio and scheduling; Part III looks at integrated, equitably efficient selection of supply portfolio and scheduling; Part IV examines integrated selection of primary and recovery supply (and demand) portfolios and scheduling; and Part V addresses disruption management of information flows in supply chains.
Author: Tadeusz Sawik Publisher: Springer Nature ISBN: 3030448142 Category : Business & Economics Languages : en Pages : 487
Book Description
This book deals with stochastic combinatorial optimization problems in supply chain disruption management, with a particular focus on management of disrupted flows in customer-driven supply chains. The problems are modeled using a scenario based stochastic mixed integer programming to address riskneutral, risk-averse and mean-risk decision-making in the presence of supply chain disruption risks. The book focuses on integrated disruption mitigation and recovery decision-making and innovative, computationally efficient multi-portfolio approach to supply chain disruption management, e.g., selection of primary and recovery supply portfolios, demand portfolios, capacity portfolios, etc. Numerous computational examples throughout the book, modeled in part on realworld supply chain disruption management problems, illustrate the material presented and provide managerial insights. Many propositions formulated in the book lead to a deep understanding of the properties of developed stochastic mixed integer programs and optimal solutions. In the computational examples, the proposed mathematical programming models are solved using an advanced algebraic modeling language such as AMPL and CPLEX, GUROBI and XPRESS solvers. The knowledge and tools provided in the book allow the reader to model and solve supply chain disruption management problems using commercially available software for mixed integer programming. Using the end-of chapter problems and exercises, the monograph can also be used as a textbook for an advanced course in supply chain risk management. After an introductory chapter, the book is then divided into six main parts. Part I addresses selection of a supply portfolio; Part II considers integrated selection of supply portfolio and scheduling; Part III looks at integrated, equitably efficient selection of supply portfolio and scheduling; Part IV examines integrated selection of primary and recovery supply and demand portfolios and production and inventory scheduling, Part V deals with selection of resilient supply portfolio in multitier supply chain networks; and Part VI addresses selection of cybersecurity safequards portfolio for disruption management of information flows in supply chains.
Author: Sushil Publisher: Springer ISBN: 8132223802 Category : Business & Economics Languages : en Pages : 338
Book Description
This edited book provides a conceptual framework of managing flexibility in the areas of people, process, technology and business supported by researches/case applications in various types of flexibilities in business. The book is organized into following five parts: (i) Managing Flexibility; (ii) People Flexibility; (iii) Process Flexibility; (iv) Flexibility in Technology and Innovation Management; and (v) Business Flexibility. Managing flexibility at the level of people, process, technology and business encompasses the requirements of both choice and speed. The need for managing flexibility is growing to cope with the developments and challenges in the global business environment. This can be seen from reactive as well as proactive perspectives. Flexibility is a major dimension of business excellence and deals with a paradoxical view point such as stability and dynamism, continuity and change, centralization and decentralization, and so on. It needs to be managed at the levels of people, process, technology and various business functions and it is important to create flexibility at the level of people to create and manage flexibility in processes and technologies in order to support flexible business requirements.
Author: Publisher: ISBN: Category : Languages : en Pages :
Book Description
This thesis attempts to integrate the three supplier processes- supplier segmentation, supplier selection/evaluation and order allocation- based on a case study of a white goods manufacturer. These processes are dealt with in a hierarchical manner, where the decisions at an earlier stage (supplier segmentation) may affect on the results of later stages (supplier selection/evaluation and order allocation). Based on a wide set of variables gathered from the supplier segmentation literature and from the framework developed by the case company, a factor analysis is performed. The resulting eight factors (complexity and criticality, supply market dynamism, supplier’s economic dependence, buyer’s supplier dependence, uncertainty, supplier capabilities, supplier’s specialization to white goods manufacturer and possibility of harm to user) are used for clustering analysis with the K-means method. Three different clustering schemes (4-clusters, 8-clusters, and 18-clusters) are analyzed to see the effect of number of clusters on the cluster means. A supplier selection model is constructed by the PROMETHEE method as was done in a former study at the same company. Two different scenarios are considered in the supplier selection phase: First, data from the former study are kept as they are. The second scenario considers a change of criteria weights. As a result, the qualified suppliers were found to be the same in both scenarios, but the rankings and net flows, which were inputs to the order allocation model, changed. The effects of these changes were discussed at a conceptual level, due to a lack of case data for the order allocation model.
Author: Lixin Cui
Author: Lixin Cui
Author: Lixin Cui (Ph. D.)
Author: Lixin Cui (Ph. D.)
Author: Mariya A. Sodenkamp 
Author: National Research Council
Author: Tadeusz Sawik
Author: Tadeusz Sawik
Author: Sushil
Author: Abraham Charnes
Author: