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Application of interactive possibilistic linear programming to aggregate production planning with multiple imprecise objectives

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PRODUCTION PLANNING & CONTROL 2007年第7期18卷 548-560页

作者： Liang, T.-F. Hsiuping Inst Technol Dept Ind Engn & Management Dali City 412 Taichung Taiwan

Aggregate production planning (APP) addresses matching supply to forecast demand, with varying customer orders over the intermediate planning horizon. In real-world APP problems, input data and related parameters are commonly imprecise because information is incomplete or unavailable, and the decision maker (DM) must simultaneously consider conflicting objectives. This study develops an interactive possibilistic linear programming (i-PLP) approach to solve multi-product and multi-time period APP problems with multiple imprecise objectives and cost coefficients by triangular possibility distributions in uncertain environments. The imprecise multi-objective APP model designed here seeks to minimise total production costs and changes in work-force level with reference to imprecise demand, cost coefficients, available resources and capacity. Additionally, the proposed i-PLP approach provides a systematic framework that helps the decision-making process to solve fuzzy multi-objective APP problems, enabling a DM to interactively modify the imprecise data and parameters until a set of satisfactory solutions is derived. An industrial case demonstrates the feasibility of applying the proposed approach to a practical multi-objective APP problem.

关键词： possibilistic linear programming aggregate production planning fuzzy set theory multi-objective linear programming

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A heuristic algorithm for master planning that satisfies multiple objectives

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COMPUTERS & OPERATIONS RESEARCH 2007年第11期34卷 3491-3513页

作者： Chern, C.-C. Hsieh, J.-S. Natl Taiwan Univ Dept Informat Management Taipei 106 Taiwan

This study proposes a heuristic algorithm, called the multi-objective master planning algorithm (MOMPA), to solve master planning (MP) problems for a supply chain network with multiple finished products. MOMPA has three objectives: to minimize delay penalties, to minimize use of outsourcing capacity, and to minimize the costs of materials, production, processing, transportation, and inventory holding-all while respecting the capacity limitations and the demand deadlines of all those involved in a given supply chain network. MOMPA plans each demand, one by one, without backtracking, and sorts those demands using a sorting mechanism that is part of the algorithm. For each demand, the minimum production cost tree is determined within the limits of the time bucket for the demand deadline. The maximum available capacity of this tree is then computed for the "no delay" case. Following this calculation, the delay-or-not criterion is evaluated to determine whether or not further delay is necessary. MOMPA compares the results of these two procedures and allocates the appropriate capacities to the demand for all the nodes on the selected tree. If the minimum cost production tree has no available capacity, MOMPA adjusts the network and looks for a new tree. With complexity and computational analysis, MOMPA is shown to be very efficient in solving NIP problems, sometimes generating the same optimal solution as the LP model. (C) 2006 Elsevier Ltd. All rights reserved.

关键词： advance planning and scheduling (APS) supply chain management master planning order scheduling demand fulfillment multi-objective linear programming

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Imprecise aggregate production planning decisions using interactive possibilistic linear programming

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JOURNAL OF STATISTICS & MANAGEMENT SYSTEMS 2007年第3期10卷 451-472页

作者： Liang, Tien-Fu Hsiuping Inst Technol Dept Ind Engn & Management 11 Gungye Rd Dali City 412 Taichung Taiwan

The goal and model inputs when applies any of conventional techniques to APP decisions are generally assumed to be deterministic/crisp, and the major limitation of these techniques is that they do not consider the time value of money for each of operating cost categories. This work presents an interactive possibilistic linear programming (PLP) method for the solving the aggregate production planning (APP) problems with imprecise goal, forecast demand, related capacities and operating costs in uncertain environments. The imprecise APP model designed here attempts to minimize total manufacturing costs with reference to inventory, labor, overtime, subcontracting and backordering levels, machine capacity, warehouse space, and the time value of money for each of the operating cost categories. The proposed PLP method achieves greater computational efficiency by employing the simplified triangular distribution to specify imprecise goal and related coefficients. The analytical results obtained by implementing a real industrial case indicate that the proposed PLP method is practically applicable for solving the practical APP problems in uncertain environments.

关键词： Aggregate production planning possibilistic linear programming fuzzy sets theory multi-objective linear programming

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Application of analytic hierarchy process in multi-objective mixed integer programming for airlift capacity planning

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ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH 2006年第1期23卷 61-76页

作者： Stannard, B Zahir, S Rosenbloom, ES Univ Lethbridge Fac Management Lethbridge AB T1K 3M4 Canada Univ Manitoba IH Asper Sch Business Winnipeg MB R3T 2N2 Canada

The analytic hierarchy process is combined with multi-objective mixed integer programming to determine the optimal allocation of a limited number of aircraft among a group of airlift users with varying levels of priority and length of usage. Canadian Forces airlift planners typically encounter such a capacity planning problem. The solution to this problem requires the constrained assignment of n variable length missions (tasks) integrating hundreds of airlift requests from several users with many priorities to m airframes (parallel machines).

关键词： decision model AHP scheduling sequencing capacity planning multi-objective linear programming mixed integer programming

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Economic profitability analysis of demand side management program

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ENERGY CONVERSION AND MANAGEMENT 2005年第18-19期46卷 2919-2935页

作者： Sheen, JN Cheng Shiu Univ Dept Elect Engn Kaohsiung Taiwan

This study considers both the internal and external costs of the utility in deriving the avoided capacity cost (ACC) and avoided operating cost (AOC) induced in an electric utility caused by the implementation of a demand side management program (DSM). In calculating the ACC, a multiple objective linear programming model is developed. Meanwhile, the AOC is calculated by considering the differences between the total and specific time period energy consumption ratios before and after the implementation of the DSM program. This study also develops an economic analysis method using Net Present Value and Pay Back Year models to assess the economic profitability of implementing a DSM program from a participant's point of view. The design and construction of a partial load leveling eutectic salt Cooling Energy Storage (CES) air conditioning system in a target office building in Kaohsiung, Taiwan, is discussed in order to simulate the cost benefit of the CES system from the perspective of the utility and from that of the participant. The results confirm the effectiveness of the developed models in simulating the economic benefits of implementing a DSM program from the perspectives of both the utility and the participant. (c) 2005 Elsevier Ltd. All rights reserved.

关键词： avoided cost multi-objective linear programming air pollution cost cooling energy storage air conditioner

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A multi-objective approach to determine alternative targets in data envelopment analysis

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JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 2004年第10期55卷 1090-1101页

作者： Lins, MPE Angulo-Meza, L da Silva, ACM Univ Fed Rio de Janeiro COPPE BR-21945 Rio De Janeiro Brazil

The choice for radial projections of classic data envelopment analysis (DEA) models, resulting in a number of projections onto the Pareto-inefficient portion of the frontier, has been seen lately as a disadvantage in DEA. The search for a non-radial projection method resulted in developments such as preference structure models. These models consider a priori preference incorporation, using weights in the search for the most preferred efficient target, although presenting some implementation difficulties. In this paper, we propose a multi-objective approach that determines the bases for a posteriori preference incorporation, through individual projections of each variable ( input or output) as an objective function, thus allowing one to obtain a target at every extreme-efficient point on the frontier. This multi-objective approach is shown to be equivalent to the preference structure models, yet presenting some advantages, such as the mapping of the possible weights, assigned to partial efficiencies of an observed unit, in order to reach a specific target.

关键词： data envelopment analysis multi-objective linear programming

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Formulation of fuzzy linear programming problems as four-objective constrained optimization problems

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APPLIED MATHEMATICS AND COMPUTATION 2003年第2-3期139卷 383-399页

作者： Zhang, GQ Wu, YH Remias, M Lu, J Curtin Univ Technol Dept Math & Stat Perth WA 6845 Australia Univ Technol Sydney Dept Software Engn Broadway NSW Australia

This paper concerns the solution of fuzzy linear programming (FLP) problems which involve fuzzy numbers in coefficients of objective functions. Firstly, a number of concepts of optimal solutions to FLP problems are introduced and investigated. Then, a number of theorems are developed so as to convert the FLP to a multi-objective optimization problem with four-objective functions. Finally, two illustrative examples are given to demonstrate the solution procedure. It also shows that our method of solution includes an existing method as a special case, (C) 2002 Elsevier Science Inc. All rights reserved.

关键词： optimization fuzzy number linear programming multi-objective linear programming

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A multi-objective model for purchasing raw materials of a large-scale integrated of bulk steel plant

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2003年第3期83卷 325-334页

作者： Gao, Z Tang, LX Northeastern Univ Sch Informat Sci & Engn Shenyang 110004 Peoples R China

The cost of purchasing raw materials and components accounts for a significant fraction in the production and manufacturing industry. Modeling of purchasing issues and hence using quantitative methods to study the purchasing issues are significant for a purchasing decision-maker (DM) with comparable schemes. This paper is grounded on purchasing of bulk raw materials of a certain large-scale steel plant. It establishes a multi-objective linear programming model (MOLP) for the special issues of purchasing these raw materials, and indicates selecting items, selecting vendors and deciding ordering quantity as the key issue in optimizing purchasing policies. A kind of multi-objective optimal method, the point estimate weighted-sums, is used to solve this model. A group of really numeral computational results show that the model is effective and can take effect on the determination. of purchasing decision. In the end of this paper, the future research directions on purchasing of raw materials are pointed out. (C) 2003 Published by Elsevier Science B.V.

关键词： purchasing multi-objective linear programming point estimate weight-sums method efficient solution

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Optimizing the management of soil erosion

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WATER QUALITY RESEARCH JOURNAL OF CANADA 2002年第3期37卷 577-586页

作者： Nikkami, D Elektorowicz, M Mehuys, GR Concordia Univ Montreal PQ H3G 1M8 Canada McGill Univ Ste Anne De Bellevue PQ H9X 1C0 Canada

To reduce the environmental and economical impact of soil erosion resulting from improper management of land-use activities, a study was initiated by the Iranian Ministry of Construction on Syahrood, one of the sub-basins of the Damavand watershed in Iran. Land-use optimization is one of the appropriate strategies for soil conservation. It can empower the decision maker or watershed manager to choose from different land-use scenarios to reach the best decision with the different combinations of variables. The output results of the sediment yield model, including the integration of the Modified Universal Soil Loss Equation (MUSLE) with Spatial Analysis System-Geographic Information System (SPANS-GIS), along with the net income of each land use were used as input in the land-use optimization model for minimizing the sediment yield and maximizing farm production of each land use. The multi-objective linear programming simplex method of Steuer (1995) was used to solve the problem. The optimization process allocated dryland farming, areas to rangelands if no changes were made to the current supporting practice system. The expected annual sediment yield from the entire sub-basin was reduced by 2420 tonnes/year (or by 5%) and the annual net farm income was increased by 3.99 billion Iranian Rial/year (or by 134%).

关键词： soil erosion sediment yield optimization multi-objective linear programming

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Production Planning Method for Supporting Processing Business in Petrochemistry

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IFAC Proceedings Volumes 2001年第8期34卷 439-444页

作者： Cornel Resteanu Electra Mitan Simion Masei National Institute for Research and Development in Informatics - (ICI) 8-10 Averescu Avenue 71316 Bucharest 1 Romania

This paper presents a cooperative production planning method. The method is mainly based on a horizontal decomposition, every department of the plant cooperates in order to obtain a good global plan. Coordination is made by the plant managers. The departments will solve multi-objective linear programming problems. In this process a large number of goals is under attention, including goals expressed by expert knowledge. A production plan with high quality technical and economic features can be very fast constructed in order to extend through worldwide the processing business of petrochemical plants

关键词： Production Planning Large Scale Systems multi-objective linear programming Expert Knowlegde Processing Systems Open to Business Decision Support Systems

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