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A Genetic Algorithm based Hybrid Approach to Solve Multi-objectiveInterval Assignment Problem by Estimation Theory
Objectives: In industrial organization and management science, Assignment Problem (AP) is most studied problem with multiple uncertain objectives; normally this uncertainty is represented by an interval. The main aim of this paper is to find a solution of such Multi-objective Interval Assignment Problem (MOIAP). Methods/Statistical analysis: This paper proposes a Genetic Algorithm (GA) based hybrid approach to solve MOIAP by using point and interval estimation theory. Estimation theory is used to manage such uncertainty with sampling. For that the samples are taken from the past data and find point estimation form the samples of each parameter to specified the range of interval with confidence level and this range is considered as an interval in AP. Findings: Traditional method like fuzzy, weighted min-max, goal programming is utilized by several researchers for find solution of MOIAP but here GA provided a proper analysis based solution. In this paper realistic example is provided to represents the solution effectiveness by estimation theory which shows that developed approach provide improved and analysis based solution compare to other approach.
Confidence Interval, Genetic Algorithm, Interval Estimation, Multi-objective Assignment Problem, Point Estimation.
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