Agent-based project scheduling

Agent technology offers a new way of thinking about many of the classic problems in operations research. Among these are problems such as project scheduling subject to resource constraints. In this paper, we develop and experimentally evaluate eight agent-based algorithms for solving the multimode,...

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Bibliographic Details
Published in:IIE transactions Vol. 32; no. 5; pp. 387 - 401
Main Authors: KNOTTS, GARY, DROR, MOSHE, HARTMAN, BRUCE C.
Format: Journal Article
Language:English
Published: Norcross Taylor & Francis Group 01.05.2000
Taylor & Francis Ltd
Subjects:
Algorithms
Job shops
Operations research
Priorities
Project management
Scheduling
Simulation
Studies
ISSN:0740-817X, 2472-5854, 1545-8830, 2472-5862
Online Access:Get full text
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Summary:Agent technology offers a new way of thinking about many of the classic problems in operations research. Among these are problems such as project scheduling subject to resource constraints. In this paper, we develop and experimentally evaluate eight agent-based algorithms for solving the multimode, resource-constrained project scheduling problem. Our algorithms differ in the priority rules used to control agent access to resources. We apply our approach to a 51-activity project originally published by Maroto and Tormos [1] We solve the problem using two types of agent-based systems: (i) a system of simple, reactive agents that we call basic agents; and (ii) a system of more complex, deliberative agents that we call enhanced agents. Of the eight priority rules tested, we find that priority based on shortest processing time performs best in terms of schedule quality when applied by basic agents while the priority based on earliest due date performs best when applied by enhanced agents. In comparing agents across priority rules, we find that enhanced agents generate much better schedules (with makespans up to 66% shorter in some cases) and require only slightly more computation time
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ISSN:0740-817X
2472-5854
1545-8830
2472-5862
DOI:10.1080/07408170008963915