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...
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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.
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 condi...
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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.
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 f...
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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.
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 co...
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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.
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 keepi...
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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.
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...
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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.
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 prof...
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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.
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 c...
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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.
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 algori...
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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.
Conventional schemes of rollback recovery with checkpointing for concurrent processes have overlooked an important problem: contamination of checkpoints as a result of error propagation among the cooperating processes...
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Conventional schemes of rollback recovery with checkpointing for concurrent processes have overlooked an important problem: contamination of checkpoints as a result of error propagation among the cooperating processes. Error propagation is unavoidable due to imperfect detection mechanisms and random interprocess communications, and it could give rise to contaminated checkpoints which, in turn, result in unsuccessful rollbacks. To counter the problem of error propagation, a damage assessment model is developed to estimate the correctness of saved checkpoints under various circumstances. Using the result of damage assessment, determination of the "optimal" checkpoints for rollback recovery-which minimize the average total recovery overhead-is formulated and solved as a nonlinear integer programming problem. Integration of damage assessment into existing recovery schemes is also discussed.
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