NDLI: Improving Multi-agent Evolutionary Techniques with Local Search for Job Shop Scheduling Problem

Content Provider	IEEE Xplore Digital Library
Author	Balid, A. Minz, S.
Copyright Year	2008
Description	Author affiliation: Sch. of Comput. & Syst. Sci., Jawaharlal Nehru Univ., New Delhi (Balid, A.; Minz, S.)
Abstract	Scheduling is the allocation of shared resources over time in order to perform a number of tasks. Job Shop Scheduling Problem (JSSP) is the most commonly encountered scheduling problem. A wide range of approaches have been proposed to solve it. In this paper two multi-agent based evolutionary models are proposed to tackle JSSP. The first one is Multi-Agent based Genetic Algorithm (MAGA) and the second model is a Multi-Agent Particle Swarm Optimization (MAPSO). A proposed local search technique as self-learning procedure for agents is hybridized with both of the multi-agent models to enhance their efficiency. The proposed models have been implemented using REPAST toolkit. Encouraging results from both models have been obtained for standard benchmarks from OR library.
Starting Page	516
Ending Page	521
File Size	383828
Page Count	6
File Format	PDF
ISBN	9780769534961
DOI	10.1109/WIIAT.2008.191
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-09
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Job shop scheduling Computational modeling Job Schop Scheduling Evolutionary computation Genetic Algorithm Approximation methods Particle swarm optimization Intelligent agent Genetic algorithms Processor scheduling Multi-Agent System Simulated annealing Resource management Particle Swarm Optimization
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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