Project Scheduling: A Memetic Algorithm with Diversity-Adaptive Components that Optimizes the Effectiveness of Human Resources

 

Virginia Yannibelli and Analía Amandi

 

ISISTAN Research Institute, UNICEN University, Tandil, Argentina, and also with CONICET, National Council of Scientific and Technological Research, Argentina (e-mail: virginia.yannibelli@isistan.unicen.edu.ar, analia.amandi@isistan.unicen.edu.ar).

 

Manuscript received on June 23, 2015
Accepted on September 30, 2015
Published on October 15, 2015

 

Abstract

In this paper, a project scheduling problem is addressed. This problem supposes valuable assumptions about the effectiveness of human resources, and also considers a priority optimization objective for project managers. This objective is optimizing the effectiveness levels of the sets of human resources defined for the project activities. A memetic algorithm is proposed for solving the addressed problem. This memetic algorithm incorporates diversity-adaptive components into the framework of an evolutionary algorithm. The incorporation of these components is meant for improving the performance of the evolutionary-based search, in both exploitation and exploration. The performance of the memetic algorithm on instance sets with different complexity levels is compared with those of the heuristic search and optimization algorithms reported until now in the literature for the addressed problem. The results obtained from the performance comparison indicate that the memetic algorithm significantly outperforms the algorithms previously reported.

Key words: Project scheduling, human resource assignment, multi-skilled resources, memetic algorithms, evolutionary algorithms, simulated annealing algorithms.

 

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