Method and system for scheduling parallel processing machines based on hybrid shuffled frog leaping algorithm and variable neighborhood search algorithm

    公开(公告)号:US10401840B2

    公开(公告)日:2019-09-03

    申请号:US15958932

    申请日:2018-04-20

    Abstract: A method and a system for scheduling parallel machines based on hybrid shuffled frog leaping algorithm and variable neighborhood search algorithm are provided to solve collaborative production and processing of jobs on a plurality of unrelated batch processing machines. The jobs are distributed to machines based on the normal processing time and deterioration situation of the jobs on different machines and are arranged. An effective multi-machine heuristic rule is designed according to the structural properties of an optimal solution for the single-machine problem, and the improved rule is applied to the improved shuffled frog leaping algorithm to solve this problem. The improvement strategy for the traditional shuffled frog leaping algorithm is to improve the local search procedure of the traditional frog leaping algorithm by introducing the variable neighborhood search algorithm. The convergence rate and optimization capacity of the original algorithm are thus improved.

    PRODUCTION SCHEDULING METHOD AND SYSTEM BASED ON IMPROVED ARTIFICIAL BEE COLONY ALGORITHM AND STORAGE MEDIUM

    公开(公告)号:US20190080270A1

    公开(公告)日:2019-03-14

    申请号:US16127124

    申请日:2018-09-10

    Abstract: The present invention disclose a parallel machine batch scheduling method and system based on an improved artificial bee colony algorithm in a deterioration situation. With this method, a near-optimal solution for the parallel machine batch scheduling problem with deteriorating jobs and maintenance consideration can be obtained. The model of the present invention is derived from an actual production process with considerations of machine maintenance and batching as well as additional processing and maintenance time for jobs and machines over time in actual production. According to the present invention, the settlement of this problem is conducive to providing reliable decision support for the production and maintenance of an enterprise in complex real production conditions, thus reducing enterprise operation costs, increasing enterprise productivity, and promoting building of a modern smart factory of the enterprise.

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