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MINIMIZING VARIATION OF PRODUCTION-RATES IN JUST-IN-TIME SYSTEMS - A SURVEY

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 1993年第3期66卷 259-271页

作者： KUBIAK, W MEM UNIV NEWFOUNDLAND FAC BUSINESS ADM St John A1B 3X5 NEWFOUNDLAND CANADA

In the past several years, there has been growing interest in scheduling problems where jobs are penalized both for being early and for being tardy. This notable deviation from previous work, in which finishing early is generally regarded as being at least as desirable as finishing on time, is perceived to be the one that well captures the scheduling dimension of JIT production systems. A number of excellent surveys on these problems has appeared over the last four years. There is, however, another important scheduling objective in JIT production systems which is to minimize variation of rates at which processes supply their outputs. These scheduling problems are, for example, of primary concern in the Toyota JIT system. Thus far, most research efforts in this area have been focused on minimizing variation of the rate at which different products are being produced on the final, multi-model assembly line which itself is a supplying process. We shall review the results of this research, and relate them to the due date based scheduling problems. Extensions and open problems will also be reviewed. Schedules that minimize variation of the rate at which different products are being produced on the line do not necessarily minimize variation in the line demand for outputs of processes that supply it. Few heuristics for the problem of minimizing the variation are available and hardly anything is known on its complexity as wel as exact algorithms to tackle it. We shall review a mathematical programming model of the problem and open questions that result from it.

关键词： PRODUCTION SCHEDULING JUST-IN-TIME nonlinear integer programming MIXED-MODEL ASSEMBLY LINES ALGORITHMS COMPUTATIONAL COMPLEXITY

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Lagrangean methods for the 0-1 Quadratic Knapsack Problem

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 1996年第2期92卷 326-341页

作者： Michelon, P Veilleux, L COLL MIL ROYAL ST JEAN ST JEANPQ J0J 1R0CANADA

It is well known that the Lagrangean decomposition provides better bounds than the Lagrangean relaxation does. Nevertheless, the Lagrangean decomposition bound is harder to compute than the Lagrangean relaxation bound. Thus, one might wonder what is the best Lagrangean method to use in a branch-and-bound algorithm. In this paper, we give an answer to such a question for the 0-1 Quadratic Knapsack Problem. We first study the Lagrangean decomposition for this problem and give new necessary optimality conditions for the dual problem which allow us to elaborate a heuristic method for solving the Lagrangean decomposition dual problem. We then introduce this method in Chaillou-Hansen-Mahieu's branch-and-bound algorithm where upper bounds were computed by Lagrangean relaxation.

关键词： nonlinear integer programming Lagrangean methods branch-and-bound algorithm

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Fuzzy Portfolio Selection Including Cardinality Constraints and integer Conditions

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JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 2016年第1期170卷 343-355页

作者： Calvo, Clara Ivorra, Carlos Liern, Vicente Univ Valencia Valencia Spain

This paper is concerned with a fuzzy version of the portfolio selection problem, which includes diversification conditions and incorporates investor's subjective preferences. The inclusion of diversification conditions leads to mixed-integer models, which are computationally demanding. On the other hand, the consideration of integer conditions makes the solution very sensitive to investor's subjective preferences with regard to the trade-off between risk and expected return. These preferences are imprecise by their very nature. In this paper, we overcome these issues by proposing a solution method for a fuzzy quadratic portfolio selection model with integer conditions. The suitability of the proposed method is illustrated by means of two numerical examples.

关键词： Fuzzy optimization Portfolio selection Efficient frontier nonlinear integer programming

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A GRASP for simultaneously assigning and sequencing product families on flexible assembly lines

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ANNALS OF OPERATIONS RESEARCH 2013年第1期203卷 295-323页

作者： Heath, Susan K. Bard, Jonathan F. Morrice, Douglas J. USN Postgrad Sch Monterey CA 93943 USA Univ Texas Austin Grad Program Operat Res & Ind Engn Austin TX 78712 USA Univ Texas Austin McCombs Sch Business Austin TX 78712 USA

This paper introduces a new model and solution methodology for a real-world production scheduling problem arising in the electronics industry. The production environment is a high volume, just-in-time, make-to-order facility with volatile demand over many product families that are assembled on flexible lines. A distinguishing characteristic of the problem is the presence of non-traditional sequence-dependant setup costs, which complicate our ability to find high-quality solutions. The scheduling problem arose when product variety exceeded the mix that the existing lines could accommodate. A nonlinear integer programming formulation is presented for the problem of minimizing setup costs, and a greedy randomized adaptive search procedure (GRASP) is developed to find solutions. To select the GRASP parameter values, an efficient, space-filling experimental design method is used based on nearly orthogonal Latin hypercubes. The proposed methodology is tested on actual factory data and compared to a prior heuristic presented in the literature;our heuristic provides a cost savings in 7 out of the 10 cases examined, and an average improvement of 17.39 % which is shown to be highly statistically significant. This improvement is due in part to the introduction of a pre-processing step to determine preferential and non-preferential line assignment information.

关键词： GRASP Production sequencing Nearly orthogonal Latin hypercubes nonlinear integer programming

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Reliability optimal design problem with interval coefficients using Hybrid Genetic Algorithms

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COMPUTERS & INDUSTRIAL ENGINEERING 1998年第1-2期35卷 373-376页

作者： Taguchi, T Yokota, T Gen, M Ashikaga Inst Technol Dept Ind & Syst Engn Ashikaga 3268558 Japan

In this paper, we formulate an optimal design of system reliability problem as nonlinear integer programming (NIP) problem with interval coefficients! transform it into single objective NIP problem without interval coefficients, and solve it directly keeping the nonlinearity of the objective function based on Hybrid Genetic Algorithms (HGAs). Also, we demonstrate the efficiency of this method with Optimal Selection and Allocation problem of a System Reliability. (C) 1998 Elsevier Science Ltd. All rights reserved.

关键词： nonlinear integer programming interval coefficient Hybrid Genetic Algorithm reliability optimization

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A solution method for a resistance circuit network design with optimal power consumption problem by using genetic algorithms

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COMPUTERS & INDUSTRIAL ENGINEERING 1998年第1-2期35卷 377-380页

作者： Zheng, LX Yokota, T Gen, M Huaqiao Univ Dept Elect Tech Fujian 362011 Peoples R China Ashikaga Inst Technol Dept Ind & Syst Engn Ashikaga 326 Japan

In this paper, we formulate a resistance circuit network design problem with optimal power consumption for a constrained electric current as a nonlinear integer programming (NIP) problem and solve it directly by keeping the nonlinear constraint based on genetic algorithms (GA). We discuss the efficency between the proposed method and Kuhn-Tucker discretized optimality criteria methods. (C) 1998 Elsevier Science Ltd. All rights reserved.

关键词： resistance circuit network nonlinear integer programming genetic algorithm

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Optimal scheduling of inspection times in a production process with a finite planning horizon

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APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY 2016年第6期32卷 775-791页

作者： Chipoyera, Honest Univ Witwatersrand Sch Stat & Actuarial Sci P Bag 3 ZA-2050 Johannesburg South Africa

Inspection models applicable to a finite planning horizon are developed for the following lifetime distributions: uniform, exponential, and Weibull distribution. For a given lifetime distribution, maximization of profit is used as the sole optimization criterion for determining an optimal planning horizon over which a system may be operated as well as ideal inspection times. Illustrative examples (focusing on the uniform and Weibull distributions and using Mathematica programs) are given. For some situations, evenly spreading inspections over the entire planning horizon are seen to result in the attainment of desirable profit levels over a shorter planning horizon. Scope for further research is given as well. Copyright (C) 2016 John Wiley & Sons, Ltd.

关键词： mixed nonlinear integer programming nonlinear integer programming optimal inspection times optimal planning horizon stochastic deterioration

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Cooperative green supply chain management with greenhouse gas emissions and fuzzy demand

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JOURNAL OF CLEANER PRODUCTION 2019年 208卷 1421-1435页

作者： Noh, Jiseong Kim, Jong Soo Hanyang Univ Dept Ind & Management Engn Erica Campus Ansan 15588 South Korea

Concerns about environmentally sustainable supply chain management have increased widely in recent years. As a consequence, supply chain members have cooperated with one another to make efficient contracts, frequently called green supply-chain management contracts. The purpose of this paper is to investigate one such contract between a single manufacturer and multiple retailers with limited resources for several types of products under greenhouse-gas emission regulations. Each retailer orders the products regularly within a limited budget and warehouse capacity. In response to orders, the manufacturer produces products and ships them after inspections. Demand for the products can be either known or have some uncertainty, which can best be represented using fuzzy number demand. To reflect demand properties, this paper introduces two nonlinear integer programming models, a crisp model and a fuzzy model. A genetic algorithm (GA) and hybrid genetic algorithm-pattern search (HGAS) are developed to solve the models. Numerical experiments evaluating the efficiency of the algorithms showed that the HGAS method performed better than the GA. Also observed is that the crisp model's average total costs were lower than those of the fuzzy model. The results as a whole indicate that the models can evaluate the performance of contracts and optimize cooperative green supply chain management. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Green supply chain management Greenhouse gas nonlinear integer programming Intelligent algorithm

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Scanning integer points with lex-inequalities: a finite cutting plane algorithm for integer programming with linear objective

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4OR-A QUARTERLY JOURNAL OF OPERATIONS RESEARCH 2021年第4期19卷 531-548页

作者： Conforti, Michele De Santis, Marianna Di Summa, Marco Rinaldi, Francesco Univ Padua Dipartimento Matemat Tullio Levi Civita Padua Italy Sapienza Univ Roma Dipartimento Ingn Informat Automat & Gest Rome Italy

We consider the integer points in a unimodular cone K ordered by a lexicographic rule defined by a lattice basis. To each integer point x in K we associate a family of inequalities (lex-inequalities) that define the convex hull of the integer points in K that are not lexicographically smaller than x. The family of lex-inequalities contains the Chvatal-Gomory cuts, but does not contain and is not contained in the family of split cuts. This provides a finite cutting plane method to solve the integer program min{cx:x is an element of S boolean AND Z(n)}, where S subset of R-n is a compact set and c is an element of Z(n). We analyze the number of iterations of our algorithm.

关键词： nonlinear integer programming Valid inequalities Cutting plane method

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Discrete Global Optimization Problems with a Modified Discrete Filled Function

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Journal of the Operations Research Society of China 2015年第3期3卷 297-315页

作者： Yong-Jian Yang Meng-Li He Yue-Lin Gao Department of Mathematics Shanghai UniversityShanghai 200444China Institute of Information and System Science Beifang University for NationalitiesYinchuan 750021China

This paper considers discrete global optimization *** traditional definition of the discrete filled function is modified in this *** on the modified definition,a new discrete filled function is presented and an algorithm for discrete global optimization is developed from the discrete filled *** experiments reported in this paper on several test problems with up to 200 variables have demonstrated the efficiency of the algorithm.

关键词： Filled function method Discrete global optimization nonlinear integer programming

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