JOURNAL ARTICLE
A multi-agent genetic algorithm for resource constrained project scheduling problems
Abstract
A multi-agent genetic algorithm is proposed to solve single-mode resource constrained project scheduling problems (MAGA-RCPSPs). In MAGA-RCPSPs, an agent represents a candidate solution to the RCPSP, and all agents live in a latticelike environment, with each agent fixed on a lattice point. In the experiments, benchmark problems Patterson and J30 are used. The results show that MAGA-RCPSPs has a good performance.
Keywords:
Computer science Mathematical optimization Scheduling (production processes) Benchmark (surveying) Job shop scheduling Genetic algorithm Algorithm Mathematics Machine learning Computer network Routing (electronic design automation)
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2
Cited By
0.38
FWCI (Field Weighted Citation Impact)
7
Refs
0.68
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Citation History
Topics
Resource-Constrained Project Scheduling
Social Sciences → Decision Sciences → Management Science and Operations Research
Scheduling and Optimization Algorithms
Physical Sciences → Engineering → Industrial and Manufacturing Engineering
Metaheuristic Optimization Algorithms Research
Physical Sciences → Computer Science → Artificial Intelligence
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