Title: Resource renting problem with discounted cash flows: a genetic algorithm solution

Authors: Amir Asrzad; Sina Shokoohyar

Addresses: Sharif University of Technology, Azadi AveTehran, 11365-11155, Iran ' Department of Computing and Decision Sciences, Stillman School of Business, Seton Hall University, South Orange, New Jersey, 07079, USA

Abstract: The resource renting problem, which is a class of project scheduling problems, is very similar to the resource investment problem. In the case of resource investment problems, the objective function is to make optimal resources procurement to have sufficient resources available in each period. In modelling the resource renting problem, we assume that the project's resources can be rented, making rental costs time-dependent. A standard resource renting problem tries to minimise the cost of acquiring resources, where the objective function only includes costs and does not include the interest rate. This paper has modelled the resource renting problem with discounted cash flow and solved it using a genetic algorithm. We consider the objective function to maximise the net present value of money and solve it using a genetic algorithm. The performance of the genetic algorithm is compared with exact methods. We have solved a set of standard project scheduling problems with both the genetic algorithm and exact methods. The test results are quite satisfactory.

Keywords: resource renting problem; discounted cash flows; genetic algorithm; project management.

DOI: 10.1504/IJBSR.2023.133121

International Journal of Business and Systems Research, 2023 Vol.17 No.5, pp.504 - 521

Received: 04 Mar 2021
Accepted: 10 Aug 2021
Published online: 01 Sep 2023 *

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