A genetic algorithm with local search using activity list characteristics for solving resource-constrained multiproject scheduling problem

Ikutaro Okada*, Wei Weng, Wenbai Yang, Shigeru Fujimura

*この研究の対応する著者

研究成果査読

7 被引用数 (Scopus)

抄録

In this paper, we aim to solve the resource-constrained multiproject scheduling problem (rc-mPSP), in which more than one project are scheduled simultaneously, projects share global resources, and the average project delay and total project time are minimized as objectives. In order to solve this problem by a centralized scheduling method, we present a new genetic algorithm (GA) approach. In this procedure, we follow the GA described in Okada et al. (2014) and improve its genetic operators, such as crossover and mutation, and local search so as to work better on rc-mPSP. Furthermore, in order to evaluate the proposed approach, we compare the results of the computational experiment on certain standard project instances with the several competing decentralized methods and centralized methods presented in the literature. We show that our procedure is one of the most competitive among such algorithms.

本文言語English
ページ(範囲)S34-S43
ジャーナルIEEJ Transactions on Electrical and Electronic Engineering
11
DOI
出版ステータスPublished - 2016 12 1

ASJC Scopus subject areas

  • 電子工学および電気工学

フィンガープリント

「A genetic algorithm with local search using activity list characteristics for solving resource-constrained multiproject scheduling problem」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル