An integrated hybrid metaheuristic model for the constrained scheduling problem

نویسندگان

چکیده

Several problems in the domains of project management (PM) and operations research (OP) can be classified as optimization which are classically NP-Hard. One such highly important problem is resource constrained scheduling (RCPSP). The main aim this to find a schedule lowest optimum makespan complete project, involves well precedence constraints. But, being NP-Hard, RCPSP requires exponential computational resources complexity increases. Thus, approximate techniques like intelligence (CI) based approaches provide better chances finding near optimal solutions. This paper presents usage hybrid technique using phases teaching learning-based (TLBO) metaheuristic integrated with operators crossover mutation from genetic algorithm (GA). An TLBO 2-point applied teacher learner discrete problem. Further, diversify population, enhance global search, operator applied. proposed model extensively tested on well-known benchmark test instances has been compared other seminal works. encouraging results make evident efficiency provided solution for varying magnitudes.

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ژورنال

عنوان ژورنال: IAES International Journal of Artificial Intelligence

سال: 2023

ISSN: ['2089-4872', '2252-8938']

DOI: https://doi.org/10.11591/ijai.v12.i3.pp1091-1103