Nixon Dcoutho

Publication Date


Document Type


First Advisor

Moraga, Reinaldo J.

Degree Name

M.S. (Master of Science)

Legacy Department

Department of Industrial and Systems Engineering


Industrial engineering; Operations research; Parallel computers; Production scheduling; Computer capacity--Planning; Heuristic algorithms


This thesis discusses the capability and effectiveness of a meta-heuristic for Randomized Priority Search to solve multi-objective problems. The multi-objective problem of unrelated parallel machine scheduling is considered in the thesis. The two objectives to minimize are total weighted tardiness and total weighted completion time. Two approaches are suggested to solve the problem. The first approach uses an existing construction rule in the literature named Apparent Tardiness Cost-bi heuristic, which is used as the basis for the meta-heuristic construction phase in Meta-RaPS to generate non-dominated solutions. The computational results obtained are promising when results of the meta-heuristic approach proposed are compared with those of the original construction rule. In the second approach, memory mechanism is incorporated in the construction phase of Meta-RaPS to solve the problem. The computational results obtained show that Meta-RaPS performs better with memory. This thesis illustrates that the meta-heuristic approach proposed is effective and flexible enough to generate Pareto frontiers in order to solve multi-objective scheduling problems.


Advisors: Reinaldo J. Moraga.||Committee members: Datu Buyung Agusdinata; Gary Chen; Christine Nguyen.


73 pages




Northern Illinois University

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