Bee Algorithm for Solving Yield Optimization Problem for Hard Disk Drive Component under Budget and Supplier’s Rating Constraints and Hueristic Performance Comparison

Abstract

AbstractThis research aims to optimize the yield for hard disk drive component problem using heuristic methods. This problem is constrained by the limited budget and the requirement on the suppliers rating of the components. Because of complexity of the problem, it is considered as a NP-Hard problem which can be formulated as a nonlinear integer programming problem. Three heuristics, Genetic Algorithm (GA), Ant Colony Optimization (ACO), and Bee Algorithm (BA), are proposed to solve this problem and compare heuristic performance from getting optimum percentage and computation time. Using the actual data from undisclosed HDD manufacturer, computational experiments are conducted under many budget constraints. The results from the experiments show that they can solve the problem with the same condition under reasonable time. Using accuracy, robustness and computation effort, it reveals that BA can solve the case study more efficient than ACO and GA.KeywordsHard Disk DriveCrossover RateHeuristic InformationBudget SettingState Transition RuleThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.