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An improved ant algorithm for Multi-mode Resource ConstrainedProject Scheduling Problem

Published online by Cambridge University Press:  11 July 2014

Peng Wuliang
Affiliation:
School of Economic and Management, Shenyang Ligong University, 110159 Shenyang, P.R. China. . peng-wuliang@163.com
Huang Min
Affiliation:
College of Information Science and Engineering, Northeastern University, 110819 Shenyang, P.R. China
Hao Yongping
Affiliation:
Laboratory of Advanced Manufacture and Equipment of Liaoning, Shenyang Ligong University, 110159 Shenyang, P.R. China
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Abstract

Many real-world scheduling problems can be modeled as Multi-mode Resource ConstrainedProject Scheduling Problems (MRCPSP). However, the MRCPSP is a strong NP-hard problem andvery difficult to be solved. The purpose of this research is to investigate a moreefficient alternative based on ant algorithm to solve MRCPSP. To enhance the generalityalong with efficiency of the algorithm, the rule pool is designed to manage numerouspriority rules for MRCPSP. Each ant is provided with an independent thread and endowedwith the learning ability to dynamically select the excellent priority rules. In addition,all the ants in the ant algorithm have the prejudgment ability to avoid infeasible routesbased on the branch and bound method. The algorithm is tested on the well-known benchmarkinstances in PSPLIB. The computational results validate the effectiveness of the proposedalgorithm.

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Type
Research Article
Copyright
© EDP Sciences, ROADEF, SMAI 2014

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