An adaptive crossover genetic algorithm with simulated annealing for multi mode resource constrained project scheduling with discounted cash flows

Vijay S. Bilolikar, Karuna Jain and Mahesh Sharma

International Journal of Operational Research, 2016, vol. 25, issue 1, 28-46

Abstract: This paper presents an adaptive crossover genetic algorithm with simulated annealing metaheuristic procedure for solving a multimode resource-constrained project scheduling problem with discounted cash flows for minimising costs. To solve the problem, a genetic algorithm is proposed for the global search, and simulated annealing is used for the local search. Two crossover operators are employed. A mathematical model is developed for the problem. Detailed computational experiments are performed on a standard problem set with randomly generated resource costs to evaluate the performance of the proposed hybrid approach.

Keywords: project management; resource constrained project scheduling; RCPS; genetic algorithms; simulated annealing; resource cost; adaptive crossover; discounted cash flows; mathematical modelling. (search for similar items in EconPapers)
Date: 2016
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.inderscience.com/link.php?id=73250 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijores:v:25:y:2016:i:1:p:28-46

Access Statistics for this article

More articles in International Journal of Operational Research from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().