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Optimization of Supplier Selection and Order Allocation Under Fuzzy Demand in Fuzzy Lead Time 1

17th Annual International Symposium on Knowledge and Systems Sciences (KSS)

作者： Suprasongsin, Sirin Van Nam Huynh Yenradee, Pisal Japan Adv Inst Sci & Technol Nomi Ishikawa Japan Thammasat Univ Sirindhorn Int Inst Technol Pathum Thani Thailand

ISBN: (数字)9789811028571

ISBN: (纸本)9789811028571;9789811028564

This paper deals with the problem of Supplier Selection and Order Allocation (SSOA) in a fuzzy sense. The demand and delivery lead time are treated as fuzzy numbers. The fuzzy number is first transformed into interval numbers. After doing some arithmetic operations, those fuzzy interval numbers are defuzzified to a crisp quantity. This crisp quantity is further used as an input parameter in the model. Essentially, the main approach in this paper is based on the function principle and the pascal triangular graded mean approach. The SSOA problem is constructed as a multiple Criteria Decision Making (MCDM) problem aiming to optimize the order quantities placed to many suppliers. The problem is solved by a fuzzy linear programming technique. A numerical example is also given for the illustration of the discussed issues.

关键词： Function principle Pascal triangular graded mean approach multiple-objective linear programming Supplier Selection and Order Allocation problem

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Inverse DEA under inter-temporal dependence using multiple-objective programming

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2015年第2期240卷 447-456页

作者： Jahanshahloo, G. R. Soleimani-damaneh, M. Ghobadi, S. Islamic Azad Univ Sci & Res Branch Dept Math Tehran Iran Univ Tehran Coll Sci Sch Math Stat & Comp Sci Tehran Iran Aalto Univ Sch Business Dept Informat & Serv Econ FI-00076 Helsinki Finland

This paper deals with the inverse Data Envelopment Analysis (DEA) under inter-temporal dependence assumption. Both problems, input-estimation and output-estimation, are investigated. Necessary and sufficient conditions for input/output estimation are established utilizing Pareto and weak Pareto solutions of linear multiple-objective programming problems. Furthermore, in this paper we introduce a new optimality notion for multiple-objective programming problems, periodic weak Pareto optimality. These solutions are used in inverse DEA, and it is shown that these can be characterized by a simple modification in weighted sum scalarization tool. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Data envelopment analysis Inverse DEA Inter-temporal dependence multiple-objective linear programming Efficiency

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The Traffic Police Location and Schedule Assignment Problem

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JOURNAL OF MULTI-CRITERIA DECISION ANALYSIS 2014年第5-6期21卷 315-333页

作者： Adler, Nicole Hakkert, Alfred Shalom Raviv, Tal Sher, Mali Hebrew Univ Jerusalem Sch Business Adm Mt Scopus IL-91905 Jerusalem Israel Ran Naor Fdn Adv Rd Safety Ramat HaSharon Israel Tel Aviv Univ Dept Ind Engn IL-69978 Tel Aviv Israel

The traffic police routine patrol vehicle mission is to provide service to the public, primarily through enforcement of traffic laws and assistance to road users after accidents or other calls for service. An efficient traffic police location and schedule assignment (TPLSAP) across a road network ensures that the traffic police undertake their mission effectively. In the search for effective road network cover solutions, a multiple-objective linear program is developed in the first stage with three distinct objectives. The objective functions maximize the following: (1) traffic police presence and conspicuousness;(2) police presence at blackspots where frequent traffic offences occur;and (3) the time available for proactive work. In the second stage of the TPLSAP formulation, distance and time halo effect integer linear programs produce a detailed, daily shift schedule across the planning horizon. Consequently, we formulate a routine traffic police schedule-location and activity problem, which incorporates road safety recommendations drawn from the literature, police policy and operational constraints. Finally, we apply the formulation to a case study of the interurban road network in Northern Israel, which highlights potential improvements over the current schedules. Copyright (C) 2014 John Wiley & Sons, Ltd.

关键词： multiple-objective linear programming road safety traffic police

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A λ-Cut and Goal-programming-Based Algorithm for Fuzzy-linear multiple-objective Bilevel Optimization

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IEEE TRANSACTIONS ON FUZZY SYSTEMS 2010年第1期18卷 1-13页

作者： Gao, Ya Zhang, Guangquan Ma, Jun Lu, Jie Univ Technol Sydney Fac Engn & Informat Technol Broadway NSW 2007 Australia

Bilevel-programming techniques are developed to handle decentralized problems with two-level decision makers, which are leaders and followers, who may have more than one objective to achieve. This paper proposes a lambda-cut and goal-programming- based algorithm to solve fuzzy-linear multiple-objective bilevel (FLMOB) decision problems. First, based on the definition of a distance measure between two fuzzy vectors using.-cut, a fuzzy-linear bilevel goal (FLBG) model is formatted, and related theorems are proved. Then, using a.-cut for fuzzy coefficients and a goal-programming strategy for multiple objectives, a.-cut and goal-programming-based algorithm to solve FLMOB decision problems is presented. A case study for a newsboy problem is adopted to illustrate the application and executing procedure of this algorithm. Finally, experiments are carried out to discuss and analyze the performance of this algorithm.

关键词： Bilevel programming decision making fuzzy sets goal programming multiple-objective linear programming optimization

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Asymptotic sign-solvability, multiple objective linear programming, and the nonsubstitution theorem

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MATHEMATICAL METHODS OF OPERATIONS RESEARCH 2006年第3期64卷 541-555页

作者： Cayton, L. Herring, R. Holder, A. Holzer, J. Nightingale, C. Stohs, T. Trinity Univ Math San Antonio TX USA Univ Calif San Diego La Jolla CA 92093 USA Oberlin Coll Oberlin OH 44074 USA Univ Wisconsin Madison WI 53706 USA Mills Coll Oakland CA 94613 USA Univ Nebraska Lincoln NE USA

In this paper we investigate the asymptotic stability of dynamic, multiple-objective linear programs. In particular, we show that a generalization of the optimal partition stabilizes for a large class of data functions. This result is based on a new theorem about asymptotic sign-solvable systems. The stability properties of the generalized optimal partition are used to address a dynamic version of the nonsubstitution theorem.

关键词： multiple-objective linear programming asymptotic programming sign-solvability nonsubstitution theorem computational economics

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Aggregate production planning - a multiple objective approach

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JOURNAL OF STATISTICS & MANAGEMENT SYSTEMS 2009年第2期12卷 287-303页

作者： Rosen, L. Drew Canel, Cem Univ North Carolina Wilmington Informat Syst & Operat Management Cameron Sch Bus Wilmington NC 28403 USA

Companies continuously plan their aggregate production quantities and are always faced with variations and uncertainties in demand which is one of the major inputs in those plans. Due to multiple objectives in aggregate production plans, the problem usually requires more in-depth analysis. This paper provides some insights into the most common objectives in solving aggregate production planning problems under different environments.

关键词： Aggregate production planning multiple-objective linear programming

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A weight space-based approach to fuzzy multiple-objective linear programming

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DECISION SUPPORT SYSTEMS 2003年第4期34卷 427-443页

作者： Borges, AR Antunes, CH INESC P-3000033 Coimbra Portugal ISEC Coimbra Polytech Inst P-3030601 Coimbra Portugal Univ Coimbra Dept Elect Engn P-3030030 Coimbra Portugal

In this paper, the effects of uncertainty on multiple-objective linear programming models are studied using the concepts of fuzzy set theory. The proposed interactive decision support system is based on the interactive exploration of the weight space. The comparative analysis of indifference regions on the various weight spaces (which vary according to intervals of values of the satisfaction degree of objective functions and constraints) enables to study the stability and evolution of the basis that correspond to the calculated efficient solutions with changes of some model parameters. (C) 2002 Elsevier Science B.V. All rights reserved.

关键词： multiple-objective linear programming fuzzy sets interactive methods weight space efficient solutions decision support systems

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Resource allocation based on efficiency analysis

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MANAGEMENT SCIENCE 2004年第8期50卷 1134-1144页

作者： Korhonen, P Syrjänen, M Helsinki Sch Econ Helsinki 00101 Finland

The purpose of this paper is to develop an approach to a resource-allocation problem that typically appears in organizations with a centralized decision-making environment, for example, supermarket chains, banks, and universities. The central unit is assumed to be interested in maximizing the total amount of outputs produced by the individual units by allocating available resources to them. We will develop an interactive formal approach based on data envelopment analysis (DEA) and multiple-objective linear programming (MOLP) to find the most preferred allocation plan. The units are assumed to be able to modify their production in the current production possibility set within certain assumptions. Various assumptions are considered concerning returns to scale and the ability of each unit to modify its production plan. Numerical examples are used to illustrate the approach.

关键词： resource allocation data envelopment analysis frontier analysis multiple-objective linear programming

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Using objective values to start multiple objective linear programming algorithms

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2001年第3期128卷 587-596页

作者： Arbel, A Korhonen, P Helsinki Sch Econ Helsinki 00100 Finland Tel Aviv Univ Dept Ind Engn IL-69978 Tel Aviv Israel

We introduce in this paper a new starting mechanism for multiple-objective linear programming (MOLP) algorithms. This makes it possible to start an algorithm from any solution in object:ive space. The original problem is first augmented in such a way that a given starting solution is feasible. The augmentation is explicitly or implicitly controlled by one parameter during the search process, which verifies the feasibility (efficiency) of the final solution. This starting mechanism can be applied either to traditional algorithms, which search the exterior of the constraint polytope, or to algorithms moving through the interior of the constraints. We provide recommendations on the suitability of an algorithm for the various locations of a starting point in objective space. Numerical considerations illustrate these ideas. (C) 2001 Elsevier Science B.V. All rights reserved.

关键词： multiple-objective linear programming interactive starting solution aspiration levels scalarizing functions reference direction interior-point algorithms

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Outcome space partition of the weight set in multiobjective linear programming

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JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 2000年第1期105卷 17-36页

作者： Benson, HP Sun, E Univ Florida Warrington Coll Business Adm Gainesville FL 32611 USA

Approaches for generating the set of efficient extreme points of the decision set of a multiple-objective linear program (P) that are based upon decompositions of the weight set W-0 suffer from one of two special drawbacks. Either the required computations are redundant, or not all of the efficient extreme point set is found. This article shows that the weight set for problem (P) can be decomposed into a partition based upon the outcome set Y of the problem, where the elements of the partition are in one-to-one correspondence with the efficient extreme points of Y. As a result, the drawbacks of the decompositions of W-0 based upon the decision set of problem (P) disappear. The article explains also how this new partition offers the potential to construct algorithms for solving large-scale applications of problem (P) in the outcome space, rather than in the decision space.

关键词： multiple-objective linear programming vector maximization efficient points weight set

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