A Max-Min Ant System algorithm to solve the Software Project Scheduling Problem

Broderick Crawford; Ricardo Soto; Franklin Johnson; Eric Monfroy; Fernando Paredes

doi:10.1016/j.eswa.2014.05.003

A Max-Min Ant System algorithm to solve the Software Project Scheduling Problem

Broderick Crawford, Ricardo Soto, Franklin Johnson, Eric Monfroy, Fernando Paredes

SCHOOL OF COMPUTER ENGINEERING

Research output: Contribution to journal › Article › peer-review

37 Scopus citations

Abstract

The Software Project Scheduling Problem is a specific Project Scheduling Problem present in many industrial and academic areas. This problem consists in making the appropriate worker-task assignment in a software project so the cost and duration of the project are minimized. We present the design of a Max-Min Ant System algorithm using the Hyper-Cube framework to solve it. This framework improves the performance of the algorithm. We illustrate experimental results and compare with other techniques demonstrating the feasibility and robustness of the approach, while reaching competitive solutions.

Original language	English
Pages (from-to)	6634-6645
Number of pages	12
Journal	Expert Systems with Applications
Volume	41
Issue number	15
DOIs	https://doi.org/10.1016/j.eswa.2014.05.003
State	Published - 1 Nov 2014

Keywords

Ant Colony Optimization
Project management
Software Project Scheduling Problem
Software engineering

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10.1016/j.eswa.2014.05.003

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abstract = "The Software Project Scheduling Problem is a specific Project Scheduling Problem present in many industrial and academic areas. This problem consists in making the appropriate worker-task assignment in a software project so the cost and duration of the project are minimized. We present the design of a Max-Min Ant System algorithm using the Hyper-Cube framework to solve it. This framework improves the performance of the algorithm. We illustrate experimental results and compare with other techniques demonstrating the feasibility and robustness of the approach, while reaching competitive solutions.",

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A Max-Min Ant System algorithm to solve the Software Project Scheduling Problem

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Keywords

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