A Hyper-Heuristic Ensemble Method for Static Job-Shop Scheduling
نویسندگان
چکیده
منابع مشابه
A Hyper-Heuristic Ensemble Method for Static Job-Shop Scheduling
We describe a new hyper-heuristic method NELLI-GP for solving job-shop scheduling problems (JSSP) that evolves an ensemble of heuristics. The ensemble adopts a divide-and-conquer approach in which each heuristic solves a unique subset of the instance set considered. NELLI-GP extends an existing ensemble method called NELLI by introducing a novel heuristic generator that evolves heuristics compo...
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Job Shop Scheduling is an important combinatorial optimisation problem in practice. It usually contains many (four or more) potentially conflicting objectives such as makespan and mean weighted tardiness. On the other hand, evolving dispatching rules using genetic programming has demonstrated to be a promising approach to solving job shop scheduling due to its flexibility and scalability. In th...
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In the past, many production-scheduling methods were developed to achieve high due-date and short manufacturing lead times performance. Among them, DRUMBUFFER-ROPE (DBR) has been recognized as one of the excellent solutions. However, there are some implementation constraints (e.g., time buffer determination, setup ratio evaluation, non-CCR subordination etc.) limit its implementation performanc...
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Multistart local search heuristics Remove and Reinsert that is based on a simple schedule constructing heuristics is tested on several benchmark instances of the job shop scheduling problem. The heuristics provides very good near optimal solutions within reasonably short computation time. The implementation within a plant simulation software is compared to the build-in genetic algorithm.
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ژورنال
عنوان ژورنال: Evolutionary Computation
سال: 2016
ISSN: 1063-6560,1530-9304
DOI: 10.1162/evco_a_00183