Research on Flexible Flow Shop Scheduling Problem with Limited Buffer Based on an Improved ICA Algorithm
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Abstract
To solve the limited-buffer flexible-flow shop scheduling problem (LBFFSP), a mathematical model of the LBFFSP is established, and an improved imperialist competitive algorithm (ⅡCA) is proposed as the global optimizing algorithm. The idea of simulated annealing is introduced to expand the scope of the search algorithm over the standard imperialist competitive algorithm, which joins three modifications, namely, the discretization processing operation, the reform operation, and the elite individual retention strategy. To further improve the efficiency of the algorithm in searching for the optimal solution, the initial population establishment method based on optimization objective is designed. The individual selection mechanism is added to improve the initial solution quality of the initial population by using Hamming distance. The algorithm parameters are analyzed to determine the optimum parameter values through simulation experiments. The effectiveness of the ⅡCA in solving the limited-buffer flexible flow shop scheduling problems is determined by comparing the example test results of ⅡCA with those of other algorithms.
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