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. / published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy

Finally, we study a multi-period, risk-averse inventory model. The objective is to maximize the expected pay-offs. The risk-averse behavior is modeled as to penalize the decision maker if a target-profit level is not satisfied for each financial reporting cycle. We recognize that the operational period is usually faster than the financial reporting cycle. Therefore, the financial reporting cycle can be considered as an integer times of the operational periods. We study this model under both accrual-basis accounting principle and cash-basis accounting principle. We prove that the optimal inventory policy is a state-dependent base-stock policy under the accrual-basis accounting method. We then show that the structure of an optimal policy is a complicated one for the cash-basis accounting method. / In this thesis we study three supply chain models which address downside risk from a different angle. We start with a commitment-option supply contract in a Conditional Value-at-Risk (CVaR) framework. We show that a CVaR trade-off analysis with advanced reservation can be carried out efficiently. Moreover, our study indicates how the corresponding contract decisions differ from decisions for optimizing an expected value. / Key words. Downside Risk Measure; CVaR; Risk; Loss-Averse; Dynamic Programming. / Owing to the growing globalization in economy and the advances in commerce, research in supply chain management has attracted large number of researchers in the last two decades. Yet standard treatments of supply chain models are mainly confined for the optimization of expected values with little reflection on risk considerations. Even for those that consider a risk measure in the objective function, there are quite few literatures employing downside risk measure. The downside risk measure takes into account only the part of the distribution that is below a critical value. Thus it indicates a safety-first strategy for decision maker. / The thesis is organized in five chapters. In Chapter 1, we provide the background and research motivation for considering downside risk measures in supply chain models. In Chapter 2, we study the pay-to-delay supply contracts with a Conditional Value-at-Risk (CVaR) framework. In Chapter 3, we study the loss-averse newsvendor problem. In Chapter 4, we extend the loss-averse model to a multi-period setting. We conclude the thesis in Chapter 5 with discussions for future research. / Then, we employ a loss-aversion utility function to characterize newsvendor's decision-making behavior. We find that when there is no shortage cost, the loss-averse newsvendor consistently orders less than a risk-neutral newsvendor. Further, we discover that the loss-averse newsvendor orders a constant quantity when the reference target is sufficiently large. We discuss the importance of initial inventory to achieve the target profit level. When the target is a decision variable, the newsvendor always sets the target no higher or no lower. / Ma, Lijun. / "October 2007." / Adviser: Houmin Yan. / Source: Dissertation Abstracts International, Volume: 69-08, Section: B, page: 5003. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (p. 140-154). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.

Chen, Chen. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (p. 89-94). / Abstracts in English and Chinese. / Table of Contents --- p.vi / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Literature Review --- p.6 / Chapter 2.1 --- Operations and Finance Interface --- p.6 / Chapter 2.1.1 --- Single Period Setting --- p.6 / Chapter 2.1.2 --- Multi-Period Setting --- p.11 / Chapter 2.2 --- Trade Credit --- p.13 / Chapter 2.3 --- Supply Chain Contracts --- p.14 / Chapter 3 --- The Model --- p.16 / Chapter 3.1 --- Model Description --- p.16 / Chapter 3.1.1 --- The Basic Setting --- p.17 / Chapter 3.1.2 --- The Bank Loan Setting --- p.19 / Chapter 3.1.3 --- The Trade Credit Setting --- p.19 / Chapter 3.2 --- Demand Distribution Properties --- p.22 / Chapter 4 --- Retailer's Perspective --- p.24 / Chapter 4.1 --- The Single Period Problem --- p.24 / Chapter 4.2 --- The Basic Setting --- p.33 / Chapter 4.3 --- The Bank Loan Setting --- p.37 / Chapter 4.4 --- The Trade Credit Setting --- p.43 / Chapter 4.5 --- Summary --- p.47 / Chapter 5 --- Supplier's Perspective --- p.48 / Chapter 5.1 --- Single Period Results --- p.48 / Chapter 5.1.1 --- The Basic Setting --- p.49 / Chapter 5.1.2 --- The Bank Loan Setting --- p.53 / Chapter 5.1.3 --- The Trade Credit Setting --- p.60 / Chapter 5.2 --- Two-Period Problem --- p.69 / Chapter 5.3 --- Summary --- p.71 / Chapter 6 --- Numerical Study and Insights --- p.72 / Chapter 6.1 --- The Single Period Supply Chain --- p.72 / Chapter 6.1.1 --- Impact of Different Financing Schemes --- p.73 / Chapter 6.1.2 --- Supply Chain Efficiency --- p.77 / Chapter 6.2 --- Capital Constrained Retailer in Two-Period Setting --- p.79 / Chapter 6.2.1 --- Impacts of Different Financial Schemes on the Retailer --- p.79 / Chapter 6.2.2 --- Saving for the Future --- p.82 / Chapter 6.2.3 --- Comparison of the Single- and Two-Period Settings --- p.83 / Chapter 7 --- Conclusion and Future Research --- p.84 / Appendix / A Log-concavity of Some Common Distributions --- p.87 / Bibliography --- p.89

published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy

The integration of production and distribution decisions presents a challenging problem for manufacturers trying to optimize their supply chain. At the planning level, the immediate goal is to coordinate production, inventory, and delivery to meet customer demand so that the corresponding costs are minimized. Achieving this goal provides the foundations for streamlining the logistics network and for integrating other operational and financial components of the system. In this paper, a model is presented that includes a single production facility, a set of customers with time varying demand, a finite planning horizon, and a fleet of vehicles for making the deliveries. Demand can be satisfied from either inventory held at the customer sites or from daily product distribution. A procedure centering on a reactive tabu search is developed for solving the full problem. After a solution is found, path relinking is applied to improve the results. A novel feature of the methodology is the use of an allocation model in the form of a mixed integer program to find good feasible solutions that serve as starting points for the tabu search. Lower bounds on the optimum are obtained by solving a modified version of the allocation model. Computational testing on a set of 90 benchmark instances with up to 200 customers and 20 time periods demonstrates the effectiveness of the approach. In all cases, improvements ranging from 10 - 20% were realized when compared to those obtained from an existing greedy randomized adaptive search procedure (GRASP). This often came at a three- to five-fold increase in runtime, however. A hybrid scheme that combines the features of reactive tabu search algorithm and branch-and-price algorithm is also developed. The combined approach takes advantage of the efficiency of the tabu search heuristic and the precision of the branch-and-price algorithm. Branching strategy that is suitable for the problem is proposed. Several advance techniques such as column generation heuristic and rounding heuristic are also implemented to improve the efficiency of the algorithm. Computational testing on standard data sets shows that a hybrid algorithm can practically solve instances with up to 50 customers and 8 time periods which is not possible by standard branch-and-price algorithm alone. / text

Ce projet de recherche s’inscrit dans un partenariat entre l’ANDRA (Agence Nationale pour la gestion des Déchets Radioactifs) et le LOSI de l’Institut Charles Delaunay (STMR UMR CNRS), UTT.La thèse vise à dimensionner les ouvrages de stockage vis-à-vis des divers flux industriels. Les flux concernés sont de nature variée et cela constitue l’une des caractéristiques du stockage. Les ouvrages doivent en effet être conçus pour permettre un développement progressif, à l’origine d’une coexistence de flux nucléaires (les colis de déchets nucléaires et les flux associés, telle la ventilation nucléaire) et de flux de chantiers conventionnels. Le dimensionnement des flux et la conception des ouvrages pour autoriser ces flux se trouvent donc au cœur du processus de conception du stockage.La problématique de notre partenaire industriel porte sur la conception de réseau (appelé flow path design). Notre contribution est dédiée au développement de modèles de flow path design avec de nouvelles contraintes ainsi qu’au développement de méthodes. Les extensions au modèle de base prennent en compte une flotte hétérogène, des segments interdits d’accès à certains véhicules et des coûts de construction. Différentes méthodes d'optimisation approchées ont aussi été développées et testées. Il s’agit de métaheuristiques basées sur les recherches locales, l’algorithme de colonies de fourmis ainsi que l’algorithme des abeilles. L’efficacité des méthodes est prouvée grâce à des tests sur des instances de la littérature et l’application au cas réel est faite par simulation / This research project is part of a partnership between ANDRA (National Agency for Radioactive Waste Management) and the LOSI, Institut Charles Delaunay (TSR UMR CNRS), UTT.The thesis aims to design the storage structures for various industrial flows. Flows involved are varied in nature and it is one of the characteristics of the storage. The works must be designed to effect a gradual development, from a "coactivity", that is to say, a coexistence of nuclear flux (the nuclear waste packages and the associated flow, such nuclear ventilation) and conventional flow sites. The design flow and the design of structures to allow these flows are therefore at the heart of the design process of storage.The problem of our industrial partner focuses on flow path design. Our contribution is dedicated to the development of models of flow path design with new constraints and the development of methods. Extensions to the basic model takes into account different type of vehicle, not allowed some segments and taking into account construction costs. Different optimization methods have also been developed and tested. Metaheuristics are based on local search, the ant colony algorithm and the algorithm of bees. Efficiency of methods is demonstrated through tests on literature benchmarks and application to the real case is done by simulation

Yau Man-Kuen. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (leaves 222-234). / Abstracts in English and Chinese. / Chapter Chapter 0 --- Introduction --- p.1 / Chapter PART A: --- Logistics in Hong Kong 一 Overview and Prospects / Chapter A.1 --- Study Objectives --- p.3 / Chapter A.2 --- Methodology --- p.4 / Chapter A.3 --- What is Logistics? --- p.4 / Chapter A.3.1 --- Major Trends --- p.6 / Chapter A.4 --- Key Features of the Logistics in Hong Kong & China --- p.8 / Chapter A.4.1 --- China Industry --- p.8 / Chapter A.4.2 --- National Developments in China --- p.13 / Chapter A.4.3 --- Hong Kong Industry --- p.16 / Chapter A.5 --- Growth Trends & Statistics for Hong Kong --- p.25 / Chapter A.6 --- Competitive Analysis for Hong Kong as a Logistics Hub --- p.45 / Chapter A.6.1 --- Current Industry Strengths --- p.45 / Chapter A.6.2 --- Current Industry Weaknesses --- p.46 / Chapter A.6.3 --- Competitiveness Challenges --- p.47 / Chapter A.6.4 --- Future Opportunities --- p.51 / Chapter A.7 --- Changing Conditions and Infrastructure Needs --- p.54 / Chapter A.7.1 --- Trade --- p.54 / Chapter A.7.2 --- Technology --- p.56 / Chapter A.7.3 --- Investment --- p.56 / Chapter A.7.4 --- Human Resources --- p.57 / Chapter A.7.5 --- Government and Regulation --- p.58 / Chapter A.8 --- Recommendations --- p.61 / Chapter A.9 --- Conclusions --- p.64 / Chapter A.10 --- Future Work --- p.65 / Chapter PART B: --- Inventory Management with Advance Ordering / Chapter Chapter B.1 --- Introduction --- p.66 / Chapter B.1.1 --- Overview --- p.66 / Chapter B.1.2 --- Literature Review --- p.69 / Chapter Chapter B.2 --- Model Formulation --- p.72 / Chapter B.2.1 --- Introduction --- p.72 / Chapter B.2.2 --- Mathematical Model --- p.74 / Chapter B.2.3 --- Preliminaries --- p.76 / Chapter B.2.4 --- Table of variables --- p.77 / Chapter Chapter B.3 --- Study of Window Size0 --- p.79 / Chapter B.3.1 --- Introduction --- p.79 / Chapter B.3.2 --- Mathematical Model --- p.79 / Chapter B.3.3 --- Proof of Window Size0 --- p.81 / Chapter Chapter B.4 --- Study of Window Size1 --- p.94 / Chapter B.4.1 --- Introduction --- p.94 / Chapter B.4.2 --- Mathematical Model --- p.95 / Chapter B.4.3 --- Optimal Ordering Policy for Window Size1 --- p.95 / Chapter B.4.4 --- Special Case of Uniformly Distributed Demand --- p.109 / Chapter B.4.5 --- Discussion of Fukuda's Paper --- p.114 / Chapter Chapter B.5 --- Simulation Study of Window Size1 --- p.120 / Chapter B.5.1 --- Simulation Models --- p.120 / Chapter B.5.2 --- Simulation Program Structure --- p.126 / Chapter B.5.3 --- Simulation Numerical Analysis --- p.131 / Chapter Chapter B.6 --- Simulation Study of Window Size K --- p.172 / Chapter B.6.1 --- Simulation Models --- p.172 / Chapter B.6.2 --- Simulation Program Structure --- p.179 / Chapter B.6.3 --- Simulation Numerical Analysis --- p.181 / Chapter Chapter B.7 --- Conclusion and Further Studies --- p.201 / Appendix (PART A) --- p.204 / Appendix (PART B) --- p.208 / Bibliography (PART A) --- p.222 / Bibliography (PART B) --- p.229

This research focuses on large-scale manufacturing systems having a number of stations with multiple tools and product types with different and deterministic processing steps. The objective is to determine the production quantities of multiple products and the tool requirements of each station that maximizes net profit while satisfying strategic constraints such as cycle times, required throughputs, and investment. The formulation of the problem, named OptiProfit, is a mixed-integer nonlinear programming (MINLP) with the stochastic issues addressed by mean-value analysis (MVA) and queuing network models. Observing that OptiProfit is an NP-complete, nonconvex, and nonmonotonic problem, the research develops a heuristic method, Differential Coefficient Based Search (DCBS). It also performs an upper-bound analysis and a performance comparison with six variations of Greedy Ascent Procedure (GAP) heuristics and Modified Simulated Annealing (MSA) in a number of randomized cases. An example problem based on a semiconductor manufacturing minifab is modeled as an OptiProfit problem and numerically analyzed. The proposed methodology provides a very good quality solution for the high-level design and operation of manufacturing facilities.

Thesis (MSc (Applied Mathematics))--University of Stellenbosch, 2005. / The process of modelling the fruit export infrastructure capacity of South Africa formed part of a larger project called the \Fruit Logistics Infrastructure Capacity Optimisation Study," which was coordinated by the Transportek division of the CSIR in Stellenbosch during the period August 2002 to March 2004. The aim of this project was to create efficiencies for, and enhance the competitiveness of, the South African fruit industry by improved usage of, and investment in, shared logistics infrastructure. After putting the size of the fruit industry into perspective, numerous aspects of the export process are considered in this thesis so as to be able to perform a comprehensive cost analysis of the export of fruit, including the cost of handling, cooling and transportation. The capacities of packhouses, cold stores and terminals are found and presented. This information, combined with fruit export volumes of 2003, then allow an estimation of the current utilisation of the South African ports with respect to fruit export.