Abstract
An Interval Programming Based Approach for fully uncertain Resource-Constrained Project Scheduling Problem Considering Project Manager’s Attitude toward Risk
Highlights
resource-constrained project scheduling problem (RCPSP) is one of the widely studied combinatorial optimization problem in operations research and has a NP-hard nature to solve optimally
This paper presents a novel interval programming based transformation approach for solving a fully uncertain RCPSP
In the mathematical formulation, all of the project parameters as well as the project schedules are considered as interval numbers
Summary
RCPSP is one of the widely studied combinatorial optimization problem in operations research and has a NP-hard nature to solve optimally. While dealing with the uncertainty of these project parameters, the usage of fuzzy set theory is preferred in this study instead of using a stochastic approach (or probability theory) and the uncertain project parameters/variables are represented by interval-valued numbers. Uncertainty of the project parameters may not be handled by random variables due to the lack of statistical past data In this case, fuzzy set theory may be a useful tool to study the project scheduling problems [3]. Fuzzy set theory can be utilized in such cases where the uncertain project parameters are estimated by project managers based on their expertise, knowledge and judgements Such a human expertise on these uncertain parameters may generally involve ambiguous or vague information which cannot be modelled by using stochastic or probabilistic approaches.
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