Production scheduling problems and traditional differential evolution(DE) are analyzed in this paper. Taking the minimum of total completion time as the objective function of production scheduling, a production schedu...
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Production scheduling problems and traditional differential evolution(DE) are analyzed in this paper. Taking the minimum of total completion time as the objective function of production scheduling, a production scheduling model is established for batch processes in process industry. Considering that the performance of the traditional DE algorithm is sensitive to the parameter settings, an adaptive control evolution strategy is used to control the parameter scale factor F and crossover probability CR to solve the problem of parameter settings. Taking a practical production problem as a scheduling example, the established model and adaptive DE algorithm are applied to implement the production scheduling simulation. The simulation results show that compared with the antcolonysystem(ACS) algorithm, the adaptive DE algorithm is effective and feasible.
Concave cost transhipment problems are difficult to optimally solve for large-scale problems within a limited period of time. Recently, some modern meta-heuristics have been employed for the development of advanced lo...
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Concave cost transhipment problems are difficult to optimally solve for large-scale problems within a limited period of time. Recently, some modern meta-heuristics have been employed for the development of advanced local search based or population-based stochastic search algorithms that can improve the conventional heuristics. Besides these meta-heuristics, the ant colony system algorithm is a population-based stochastic search algorithm which has been used to obtain good results in many applications. This study employs the ant colony system algorithm, coupled with some genetic algorithm and threshold accepting algorithm techniques, to develop a population based stochastic search algorithm for efficiently solving square root concave cost transhipment problems. The developed algorithms are evaluated with a number of problem instances. The results indicate that the proposed algorithm is more effective for solving square root concave cost transhipment problems than other recently designed local search based algorithms and genetic algorithm.
This paper considers the vehicle routing problem with time windows where the uncertainties of travel times are modeled with possibility distributions. A possibilistic programming model is designed for the problem. Fur...
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ISBN:
(纸本)9781424469208
This paper considers the vehicle routing problem with time windows where the uncertainties of travel times are modeled with possibility distributions. A possibilistic programming model is designed for the problem. Furthermore, an ant colony system algorithm is developed to solve the proposed model. Necessity measure is used to gain knowledge about the feasibility of generated solutions when they are realized. Finally, numerical examples are given to show the effectiveness and usefulness of the algorithm.
Dynamic transmission network expansion planning problem is a complex combinatorial optimization problem. Although this problem has been extensively studied, it is still not well solved. In recent years, antalgorithm,...
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ISBN:
(纸本)9810487908
Dynamic transmission network expansion planning problem is a complex combinatorial optimization problem. Although this problem has been extensively studied, it is still not well solved. In recent years, antalgorithm, a new metaheuristic method, is emerging. It is highly efficient for finding high quality solutions to combinatorial optimization problems. In this paper, antalgorithm is briefly introduced and firstly used to solve the dynamic transmission network expansion planning problem. The corresponding mathematical model, together with its solution algorithm, is also presented. The simulation (1)results of a sample system, although preliminary, have verified its feasibility and efficiency. The directions of future research in improving antalgorithm to solve dynamic transmission network expansion planning problems are also proposed.
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