A differential evolution algorithm with local search for resource investment project scheduling problems

Author

Song, Yanni ; Liu, Jing ; Wimmers, Martin O. ; Jiang, Zhongzhou

Author_Institution

Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi´an 710071, China

fYear

2015

fDate

25-28 May 2015

Firstpage

1725

Lastpage

1731

Abstract

In this paper, we propose a differential evolution algorithm with local search to solve the resource investment project scheduling problems (RIPSPs), labeled as DELS-RIPSP. Project tardiness is not permitted during the process of optimization. DELS-RIPSP improves the population quality by changing existing chromosomes to those with better fitness using the local search operator in order to reduce resource cost. The performance of DELS-RIPSP is validated on 450 benchmark problems, including Mohring instances and ProGen instances with 10, 14 and 20 non-dummy activities. The percentages of optimal solutions under a fixed number of evaluations are reported. The experimental results illustrate the effectiveness of the proposed algorithm and its potential for solving RIPSPs.

Keywords

Algorithm design and analysis; Investment; Scheduling; Search problems; Silicon; Sociology; Statistics; differential evolution algorithm; local search; resource investment project scheduling problems;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation (CEC), 2015 IEEE Congress on

Conference_Location

Sendai, Japan

Type

conf

DOI

10.1109/CEC.2015.7257095

Filename

7257095