Therefore, this research introduces a hybrid evolutionary framework, based on two multi-operator evolutionary algorithms, and a heuristic technique, for a multi ...
The objective of a MM-. RCPSP is to minimize the project duration by scheduling the activities with determining their best modes subject to resource and ...
Jul 16, 2024 · The aim of this paper is to suggest novel Cuckoo Search algorithm to solving Multi-Skill Resource Constrained Project Scheduling Problem (MS - ...
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Evolutionary algorithms, a form of meta-heuristic, have been successfully applied to a number of classes of complex combinatorial problems such as the ...
This project aims to develop an algorithmic framework for reactive planning under unknown disturbances and dynamic changes. There is a huge gap between current ...
We design a bi-objective evolutionary algorithm that includes problem-specific knowledge and is based on the Non-dominated Sorting Genetic Algorithm (NSGA-II).
A memetic algorithm to address the multi-node resource-constrained project scheduling problem · Hybrid evolutionary algorithm for large-scale project scheduling ...
We design a bi-objective evolutionary algorithm that includes problem-specific knowledge and is based on the Non-dominated Sorting Genetic Algorithm (NSGA-. II) ...
Abstract. This work describes a genetic algorithm approach to resource-constrained scheduling using a direct, time-based representation.
A genetic algorithm (GA) is proposed for solving the multimode resource-constrained project scheduling problem (MRCPSP) improved by a new local search method.