A hybrid TLBO-TS algorithm for integrated selection and scheduling of projects. (May 2018)

• Record Type: Journal Article
• Authors: Kumar, Manish; Mittal, M.L.; Soni, Gunjan; Joshi, Dheeraj
• Is Part Of: Computers & industrial engineering. Volume 119(2018)
• Page Start: 121
• Page End: 130
• Publication Date: 2018-05
• Subjects: Project selection and scheduling -- Meta-heuristic methods -- TLBO algorithm -- Tabu search -- Hybrid algorithms; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2018.03.029
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: The paper focuses on simultaneous selection and scheduling of interdependent projects. Two types of interdependencies: mutual exclusiveness and complementariness have been considered. A zero-one integer programming model is proposed for the problem. Three meta-heuristics: TLBO, TS and hybrid TLBO-TS have been developed. Abstract: Organizations dealing with projects often face the challenge of choosing right mix of projects for implementation and scheduling. The two steps have, however, traditionally been performed in sequential manner often resulting into problems such as scope changes/dropping/replacement/delayed completion of the projects. This paper deals with the problem of simultaneous selection and scheduling of the projects with maximization of total expected benefit of the portfolio as an objective. Expected benefit of the project is considered to be time sensitive. Further, the projects have a variety of interdependencies between them. Two types of interdependencies: mutual exclusiveness and complementariness have been considered. A zero-one integer programming model is proposed for the problem. Three meta-heuristics: TLBO, TS and hybrid TLBO-TS have been developed and compared with the existing algorithms in the literature. The performance of the algorithms is evaluated on the four different types of data sets. Performance of the hybrid TLBO-TS algorithm has been found to be quite promising in terms of solution quality and convergence.