Multi-objective optimization for the multi-mode finance-based project scheduling problem

Sameh Al-SHIHABI, Mohammad AlDURGAM

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Front. Eng ›› 2020, Vol. 7 ›› Issue (2) : 223-237. DOI: 10.1007/s42524-020-0097-1
RESEARCH ARTICLE
RESEARCH ARTICLE

Multi-objective optimization for the multi-mode finance-based project scheduling problem

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Abstract

The finance-based scheduling problem (FBSP) is about scheduling project activities without exceeding a credit line financing limit. The FBSP is extended to consider different execution modes that result in the multi-mode FBSP (MMFBSP). Unfortunately, researchers have abandoned the development of exact models to solve the FBSP and its extensions. Instead, researchers have heavily relied on the use of heuristics and meta-heuristics, which do not guarantee solution optimality. No exact models are available for contractors who look for optimal solutions to the multi-objective MMFBSP. CPLEX, which is an exact solver, has witnessed a significant decrease in its computation time. Moreover, its current version, CPLEX 12.9, solves multi-objective optimization problems. This study presents a mixed-integer linear programming model for the multi-objective MMFBSP. Using CPLEX 12.9, we discuss several techniques that researchers can use to optimize a multi-objective MMFBSP. We test our model by solving several problems from the literature. We also show how to solve multi-objective optimization problems by using CPLEX 12.9 and how computation time increases as problem size increases. The small increase in computation time compared with possible cost savings make exact models a must for practitioners. Moreover, the linear programming-relaxation of the model, which takes seconds, can provide an excellent lower bound.

Keywords

multi-objective optimization / finance-based scheduling / multi-mode project scheduling / mixed-integer linear programming / CPLEX

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Sameh Al-SHIHABI, Mohammad AlDURGAM. Multi-objective optimization for the multi-mode finance-based project scheduling problem. Front. Eng, 2020, 7(2): 223‒237 https://doi.org/10.1007/s42524-020-0097-1

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Acknowledgement

We would like to thank IBM Company for making CPLEX free for research. The second author would like to acknowledge the support provided by the Systems Engineering Department, King Fahd University of Petroleum & Minerals, Dhahran-KSA, to conduct this research.

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