Skip to main content
select distinct n.content as name, r.content as role, t.nameID as nameID, n.unitID, n.departmentID, n.facultyID, n.provinceID, n.countryID from transaction as t, Name as n, Role as r where t.itemID='749552' and and

Bee Algorithm for solving Yield optimization problem for hard disk drive component under budget and supplier's rating constraints and hueristic Performance comparison



เครือข่ายนักวิจัย+ผลงานวิจัย (full screen)


This 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. © 2011 Springer Science+Business Media, LLC.

Nonlinear integer programming problem (1 items found) | Budget constraint (7 items found) | Heuristic methods (179 items found) | NP-HARD problem (11 items found) | Bee Algorithm (11 items found) | Computational complexity | Ant-colony optimization | Performance comparison | Yield optimization | Budget control |

Source : TNRR-49418 | orignial