Abstract

Minimizing the costs in a project is highly tied with the way the required resources are provided. The resource investment problem deals with how to employ the renewable resources such that the related costs are minimized. Furthermore, the material ordering problem alludes to outlining a proper plan for supplying the nonrenewable resources (materials) to minimize the associated costs. The present paper studies the integration of the resource investment problem with the quantity discount problem in material ordering to thoroughly investigate the resource costs of projects in a single circumstance. The integrated model is presented and mathematically formulated. Three hybrid procedures are proposed for the model, each of which includes a genetic algorithm combined with a dynamic programming, a simulated annealing or a particle swarm optimization algorithm. The mathematical formulations of some small instances are solved to be the subject of an exact comparison with hybrid procedures. The proposed procedures are tested on a set of 810 benchmarks known in the literature. The computational experiments reported by algorithms validate the efficiency of the hybrid genetic algorithm and dynamic programming for the model more than other hybrid approaches.

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