An evolutionary hyper-heuristic for the software project scheduling problem

Xiuli WU*, Pietro CONSOLI, Leandro MINKU, Gabriela OCHOA, Xin YAO*

*Corresponding author for this work

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

22 Citations (Scopus)

Abstract

Software project scheduling plays an important role in reducing the cost and duration of software projects. It is an NP-hard combinatorial optimization problem that has been addressed based on single and multi-objective algorithms. However, such algorithms have always used fixed genetic operators, and it is unclear which operators would be more appropriate across the search process. In this paper, we propose an evolutionary hyper-heuristic to solve the software project scheduling problem. Our novelties include the following: (1) this is the first work to adopt an evolutionary hyper-heuristic for the software project scheduling problem; (2) this is the first work for adaptive selection of both crossover and mutation operators; (3) we design different credit assignment methods for mutation and crossover; and (4) we use a sliding multi-armed bandit strategy to adaptively choose both crossover and mutation operators. The experimental results show that the proposed algorithm can solve the software project scheduling problem effectively. © Springer International Publishing AG 2016.
Original languageEnglish
Title of host publicationParallel Problem Solving from Nature – PPSN XIV : 14th International Conference, Edinburgh, UK, September 17-21, 2016, Proceedings
EditorsJulia HANDL, Emma HART, Peter R. LEWIS, Manuel LÓPEZ-IBÁÑEZ, Gabriela OCHOA, Ben PAECHTER
PublisherSpringer
Pages37-47
Number of pages11
ISBN (Electronic)9783319458236
ISBN (Print)9783319458229
DOIs
Publication statusPublished - 2016
Externally publishedYes
Event14th International Conference on Parallel Problem Solving from Nature - Edinburgh, Scotland, United Kingdom
Duration: 17 Sept 201621 Sept 2016

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume9921
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference14th International Conference on Parallel Problem Solving from Nature
Abbreviated titlePPSN 2016
Country/TerritoryUnited Kingdom
CityScotland
Period17/09/1621/09/16

Bibliographical note

This paper was partly supported by the National Natural Science Foundation of China under Grant (Grants. 51305024 and 61329302) and EPSRC (Grant No. EP/J017515/1). Xin Yao was supported by a Royal Society Wolfson Research Merit Award.

Keywords

  • Adaptive operator selection
  • Hyper-heuristics
  • Sliding multi-armed bandit
  • Software project scheduling

Fingerprint

Dive into the research topics of 'An evolutionary hyper-heuristic for the software project scheduling problem'. Together they form a unique fingerprint.

Cite this