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A multi-objective particle swarm optimization for project selection problem
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DOI：10.1016/j.eswa.2009.05.056.png)
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摘要
En 中文
Selecting the most appropriate projects out of a given set of investment proposals is recognized as a critical issue for which the decision maker takes several aspects into consideration. Since many of these aspects may be conflicting, the problem is rendered as a multi-objective one. Consequently, we consider a multi-objective project selection problem in this Study where total benefits are to be maximized while total risk and total coat must be minimized, simultaneously. Since solving an NP-hard problem becomes demanding as the number of projects grows, a multi-objective particle swarm with new selection regimes for global best and personal best for swarm members is designed to find the locally Pareto-optimal frontier and is compared with a salient multi-objective genetic algorithm, i.e. SPEAII, based on some comparison metrics with random instances. (C) 2009 Elsevier Ltd. All rights reserved.
Keyword:
Multi-objective particle swarm
Project selection problem
Multi-objective genetic algorithm
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