Title: An efficient teaching-learning-based optimisation algorithm for the resource-constrained project scheduling problem

Authors: Dheeraj Joshi; M.L. Mittal; Manish Kumar

Addresses: Department of Mechanical Engineering, Swami Keshvanand Institute of Technology Management and Gramothan, Jaipur, India; Malaviya National Institute of Technology, Jaipur, India ' Department of Mechanical Engineering, Malaviya National Institute of Technology, Jaipur, India ' Department of Mechanical Engineering, Malaviya National Institute of Technology, Jaipur, India

Abstract: This work proposes a teaching-learning-based optimisation algorithm as an alternative metaheuristic to solve the resource-constrained project scheduling problem (RCPSP). A precedence feasible activity list is employed for encoding the solutions whereas serial schedule generation scheme (SGS) is used as the decoding procedure to derive the solutions. In order to have good initial population, we employ a regret-based sampling method with latest finish time (LFT) priority rule. In addition to teacher and learner phase in basic TLBO, the proposed work also applies two additional phases namely self-study and examination for improving its exploration and exploitation capabilities. The algorithm is tested on well-known instance sets from literature. The performance of the algorithm is found to be competitive with the existing solution approaches available to solve this problem.

Keywords: resource-constrained project scheduling; teaching-learning-based optimisation algorithm; metaheuristics.

DOI: 10.1504/IJISE.2020.106097

International Journal of Industrial and Systems Engineering, 2020 Vol.34 No.4, pp.544 - 561

Received: 21 Mar 2018
Accepted: 28 Sep 2018
Published online: 30 Mar 2020 *

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