A multiagent evolutionary algorithm for the resource-constrained project portfolio selection and scheduling problem
type: Item
instance of: scholarly article
title: A multiagent evolutionary algorithm for the resource-constrained project portfolio selection and scheduling problem
zbMATH Open document ID: 1407.90175
DOI: 10.1155/2014/302684
author: Yongyi Shou
author: Wenwen Xiang
author: Ying Li
author: Weijian Yao
published in: Mathematical Problems in Engineering
publication date: 2019-02-08T00:00:00Z
review text: Summary: A multiagent evolutionary algorithm is proposed to solve the resource-constrained project portfolio selection and scheduling problem. The proposed algorithm has a dual level structure. In the upper level a set of agents make decisions to select appropriate project portfolios. Each agent selects its project portfolio independently. The neighborhood competition operator and self-learning operator are designed to improve the agent's energy, that is, the portfolio profit. In the lower level the selected projects are scheduled simultaneously and completion times are computed to estimate the expected portfolio profit. A priority rule-based heuristic is used by each agent to solve the multiproject scheduling problem. A set of instances were generated systematically from the widely used Patterson set. Computational experiments confirmed that the proposed evolutionary algorithm is effective for the resource-constrained project portfolio selection and scheduling problem.
Mathematics Subject Classification ID: 90B35
Mathematics Subject Classification ID: 90C10
Mathematics Subject Classification ID: 90C59
Mathematics Subject Classification ID: 91G10
zbMATH DE Number: 7016116
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2014/302684
OpenAlex ID: W2003519928
Wikidata QID: Q59065628
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description: scientific article; zbMATH DE number 7016116