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A genetic algorithm for job shop scheduling with load balancing
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The load-balancing algorithm allocates jobs, split into lots, on identical machines, with objectives to reduce job total throughput time and to improve machine. This paper deals with the load-balancing of machines in a real-world job-shop scheduling problem with identical machines, and develops a genetic algorithm.
The load-balancing algorithm allocates jobs, split into lots, on identical machines, with objectives to reduce job total throughput time and to improve machine. This paper deals with the load-balancing of machines in a real-world job-shop scheduling problem with identical machines, and develops a genetic algorithm.
This paper deals with the load-balancing of machines in a real-world job-shop scheduling problem with identical machines. The load-balancing algorithm allo S. Incorporating weighted tardiness and setup-worker load balance into the objective function of the problem, we have developed a genetic algorithm (GA) using the.
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Abstract: In this paper, a Multi-Population Genetic Algorithm (MPGA) considering load balancing is adopted for solving task scheduling problems in cloud. Flexible Job Shop Scheduling Problem (FJSSP) is an extension of the classical Job Shop Scheduling Problem (JSSP). The FJSSP is known to be NP-hard problem.
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