A Multi-product, Multi-supplier, Multi-period and Multi- Price Discount Levels Supplier Selection and Order Allocation Model Under Demand Uncertainty PDF Download

Author: Swapnil Phansalkar
Publisher:
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Languages : en
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In this thesis, a multi criteria decision making model for supplier selection and order allocation is developed under demand uncertainty. The primary goal of this model is to assist the buyer in making the decision regarding the selection of suppliers and allocation of order quantities to the selected suppliers to satisfy demand for each product in every time period. The multi criteria decision making model has the following three objectives: to minimize the total cost over planning horizon, to minimize the total number of quality defects and to minimize the weighted average lead time. The demand is assumed to follow normal distribution and shortages are allowed in this model. Further, each supplier is assumed to provide all unit type of price discount for each part. A mathematical formulation is done for each objective and then a general model for multiple products, multiple suppliers, multiple time periods and multiple price discount levels is developed. The multi criteria model includes the buyer's demand constraints, the supplier's capacity constraints and the supplier's price break constraints. The following decisions are to be made in this model: to select the appropriate suppliers considering the objectives of the model and to determine the optimal order quantity from the selected suppliers to satisfy the buyer's demand for each time period. This model uses weighted objective method to determine the optimal solution to the multi criteria decision making problem.

Author: Yishan Sun
Publisher:
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Languages : en
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In this thesis, a multi-period multiple sourcing supplier selection and order allocation model under demand uncertainty condition with shortages is built. The objective is to determine which suppliers should be selected and the order quantities of each product for each period.The problem has three objectives: minimizing the total cost over the planning horizon, minimizing the weighted average lead time over the planning horizon and minimizing the weighted average quality defect rate over the planning horizon. First, a mathematical formulation for all the three objectives is developed and then a general multi-period and multi-criteria optimization model is presented.There are two key decisions to make: 1) to choose the most favorable suppliers from a given set of suppliers to meet supplier selection criteria for various items in each period; 2) to order optimal quantities in each period for each poduct from the selected suppliers to meet the production demand. Weighted Objective method is used to generate the efficient solution by assigning weights to the three criteria. A sensitivity analysis is done to study the impact of changing the input parameters values such as initial inventory levels and maximum and minimum values of demands on the total cost objective and selection of suppliers.

Author: Ziqi Ding
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Languages : en
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This thesis considers the use of multi-criteria optimization methods applied to supplier selection and order allocation problem over a planning horizon under multiple sourcing strategy. The supply chain system is modeled with a single buyer and multiple suppliers with deterministic demands as a mixed integer programming problem.We study the supplier selection and order allocation problem with three objectives. The criteria considered are (1) total cost over the planning horizon; (2) weighted average lead time and (3) weighted average quality defect rate. We first develop the mathematical formulation for all three objectives and then present a general multi-period and multi-criteria optimization model for the procurement problem.Two methods are used to solve the multi-criteria mathematical programming problem. The first approach is the Weighted Objective method. It is used to generate several efficient solutions by changing the weights assigned to the three criteria. The second approach is the Goal Programming method, which is used to generate the optimal solutions that can satisfy the specified targets set for the three criteria according to the decision maker's preference. Several efficient points are generated by both Preemptive and Non-Preemptive Goal Programming methods. A numerical example is presented to illustrate both approaches. There are fourteen efficient solutions generated from both approaches. We compare the efficient solutions visually using the Value Path Approach. A sensitivity analysis is done to study the impact of changing the weight of the non-value added cost in the total cost objective.

Author: Lixin Cui
Publisher: Open Dissertation Press
ISBN: 9781361312308
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Languages : en
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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: Yuda Chen
Publisher:
ISBN:
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Languages : en
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In this thesis, a multi-criteria multi-period supplier selection and order allocation problem is studied. The supply chain system is modeled with a single buyer and multiple suppliers with deterministic demands as a mixed integer programming problem. Five objectives are included in the multi-period and multi-sourcing problem. All-unit quantity discount policy is also incorporated in the model. The five objectives considered are (1) procurement cost; (2) weighted average inventory; (3) weighted average shortage; (4) weighted average lead time (5) weighted average quality defect rate. Model constraints include demand balance constraints, all-unit discount policy constraints and capacity constraints of the suppliers. Weighted objective method and Goal programming methods (both preemptive and non-preemptive) are utilized to solve the multi-criteria mathematical programming problem. Weighted objective method is used to generate several efficient solutions by applying different sets of weights assigned to the five criteria. In both Preemptive goal programming and Non-preemptive goal programming, the specified goals for the five objectives are satisfied according to the decision maker's preference. A numerical example is presented to illustrate the Weighted objective and Goal programming methods. Twelves efficient solutions are analyzed visually through the Value Path Approach. A sensitivity analysis is conducted to study the impact of varying inventory factors and shortage factors on the optimal sourcing decisions.

Author: Martins, Carlos
Publisher: IGI Global
ISBN: 1799818454
Category : Business & Economics
Languages : en
Pages : 267

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Book Description
The globalized economy, dominated by the diffusion of innovation and social, political, and economic changes, allows people and knowledge to flow without knowing what lies ahead. As new economies emerge and technologies impose significant changes, the internationalization of markets and industries has made defining its delimitation more difficult. Competitive Drivers for Improving Future Business Performance is a conceptualized reference source that discusses the use of digital skills to manage change in volatile contexts and provides fundamental understanding of competitive advantage to guarantee superior performances. To assure this level of performance, a set of choices (drivers) must be created ensuring operational efficiency, innovative products, customer knowledge-base, and focused branding. Featuring research on topics such as consumer experience, strategic leadership, and flexible technologies, this book is ideally designed for managers, executives, entrepreneurs, academicians, consulting professionals, researchers, industry professionals, and students seeking coverage on how to improve competitive performance in an era of uncertainty.

Author: Dmitry Ivanov
Publisher: Springer
ISBN: 3319693050
Category : Business & Economics
Languages : en
Pages : 332

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Book Description
This book offers an introduction to structural dynamics, ripple effect and resilience in supply chain disruption risk management for larger audiences. In the management section, without relying heavily on mathematical derivations, the book offers state-of-the-art concepts and methods to tackle supply chain disruption risks and designing resilient supply chains in a simple, predictable format to make it easy to understand for students and professionals with both management and engineering background. In the technical section, the book constitutes structural dynamics control methods for supply chain management. Real-life problems are modelled and solved with the help of mathematical programming, discrete-event simulation, optimal control theory, and fuzzy logic. The book derives practical recommendations for management decision-making with disruption risk in the following areas: How to estimate the impact of possible disruptions on performance in the pro-active stage? How to generate efficient and effective stabilization and recovery policies? When does one failure trigger an adjacent set of failures? Which supply chain structures are particular sensitive to ripple effect? How to measure the disruption risks in the supply chain?

Author: Bruno Vallespir
Publisher: Springer
ISBN: 3642163580
Category : Computers
Languages : en
Pages : 681

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Book Description
The present economic and social environment has given rise to new situations within which companies must operate. As a first example, the globalization of the economy and the need for performance has led companies to outsource and then to operate inside networks of enterprises such as supply chains or virtual enterprises. A second instance is related to environmental issues. The statement about the impact of ind- trial activities on the environment has led companies to revise processes, to save - ergy, to optimize transportation.... A last example relates to knowledge. Knowledge is considered today to be one of the main assets of a company. How to capitalize, to manage, to reuse it for the benefit of the company is an important current issue. The three examples above have no direct links. However, each of them constitutes a challenge that companies have to face today. This book brings together the opinions of several leading researchers from all around the world. Together they try to develop new approaches and find answers to those challenges. Through the individual ch- ters of this book, the authors present their understanding of the different challenges, the concepts on which they are working, the approaches they are developing and the tools they propose. The book is composed of six parts; each one focuses on a specific theme and is subdivided into subtopics.

Author: Mariya A. Sodenkamp
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 16

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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: Cong Guo (Industrial engineer)
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description
This article addresses the development of an integrated supplier selection and inventory control problems in supply chain management by developing a mathematical model for a multi-echelon system. In particular, a buyer firm that consists of one warehouse and N identical retailers wants to procure a type of product from a group of potential suppliers, which may require different price, ordering cost, lead time and have restriction on minimum and maximum total order size, to satisfy the stochastic demand. A continuous review system that implements the order quantity, reorder point (Q, R) inventory policy is considered in the model. The objective of the model is to select suppliers and to determine the optimal inventory policy that coordinates stock level between each echelon of the system while properly allocating orders among selected suppliers to maximize the expected profit. The model has been solved by decomposing the mixed integer nonlinear programming model into two sub-models. Numerical experiments are conducted to evaluate the model and some managerial insights are obtained by performing some sensitivity analysis.