生產(chǎn)計劃調(diào)度崗位職責(zé)-文庫吧資料
2024-10-25 01:53本頁面
【正文】 mined appropriately in advance, we search better values of them in the hybrid GA to Gas in literatures, a chromosome includes not only genes representing the relative priorities of all operations but also genes representing the parameters to determine the upper bound of idle times permitted on a given machine before scheduling an random keys representation is used to encode a element of the chromosome is a real number of [0,1].During the schedule generation phase, the SPV rule is used to convert a real number vector into a job repetition on the hybrid scheduler, a chromosome is decoded into a feasible , a local search is executed in the neighborhood determined by the critical active chain to improve the performance of the schedule generated in the schedule generation In the 2section, we present the formulation of job shop scheduling problem to minimize the 3 section, we describe the proposed hybrid genetic algorithm in the 4 section, the proposed algorithm is evaluated on benchmark , we conclude the paper with a summary in 5th section.《Hybrid Genetic Algorithm for Solving JobShop Scheduling Problem》 作者： HasanThe JobShop Scheduling Problem(JSSP)is a wellknown difficult binatorial optimization algorithms have been proposed for solving JSSP in the last few decades, including algorithms based on evolutionary , there is room for improvement in solving medium to large scale problems this paper, we present a Hybrid Genetic Algorithm(HGA)that includes a heuristic job ordering with a Genetic apply HGA to a number of benchmark is found that the algorithm is able to improve the solution the solution obtained by traditional genetic algorithm.《Scheduling jobs and maintenances in flexible job shop with a hybrid genetic algorithm》Most flexible job shop scheduling models assume that the machines are available all of the , in most realistic situations, machines may be unavailable due to maintenances, preschedules and so this paper, we study the flexible job shop scheduling problem with availability availability constraints are nonfixed in that the pletion time of the maintenance tasks is not fixed and has to be determined during the scheduling then propose a hybrid genetic alogorithm to solve the flexible job shop scheduling problem with nonfixed availability genetic algorithm uses an innovative representation method thrdand applies genetic operations in phenotype space in order to enhance the also define two kinds of neighbourhood for the problem based on the concept of critical local search procedure is then integrated under the framework of the genetic flexible job shop scheduling benchmark problems and fJSPnfa problems are solved in order to test the the effectiveness and efficiency of the suggested methodology.《A Hybrid genetic algorithm for nowait job shop scheduling problems》 作者：Jason ChaoHsien Pan, HanChiang HuangA nowait job shop describes a situation where
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