A Tabu search algorithm for simultaneous selection and scheduling of projects

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Abstract

In this paper, the problem of simultaneous selection and scheduling of projects is considered. Problem considers the time-sensitive profits, interdependencies, fixed planning horizon, and due dates of the projects. A 0–1 integer programing model is presented for the problem. The objective of the model is to maximize the total expected profit from the portfolio. The problem being NP-hard; a solution approach is required to solve the problem optimally in reasonable computational time. Thus, a TS algorithm is developed to solve the problem with a new move strategy. This strategy provides a structured neighborhood, which varies with the size of the problem. The algorithm is applied to three different sizes of the tabu list to find the right setting of tabu length to balance the exploration and exploitation during the search. Computational experiments are used to compare these three forms of the proposed TS algorithm. Fifteen test instances with different complexity levels have been developed to check the performance of the proposed TS algorithm. From the results, it is clear that tabu search is quite promising to solve the problem. Finally, some future directions are suggested for the problem.

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Kumar, M., Mittal, M. L., Soni, G., & Joshi, D. (2019). A Tabu search algorithm for simultaneous selection and scheduling of projects. In Advances in Intelligent Systems and Computing (Vol. 741, pp. 1111–1121). Springer Verlag. https://doi.org/10.1007/978-981-13-0761-4_104

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