Approximating multi-objective scheduling problems

S. Dabia, El-Ghazali Talbi, T. Woensel, van, A.G. Kok, de

Research output: Contribution to journalArticleAcademicpeer-review

15 Citations (Scopus)
5 Downloads (Pure)


In many practical situations, decisions are multi-objective by nature. In this paper, we propose a generic approach to deal with multi-objective scheduling problems (MOSPs). The aim is to determine the set of Pareto solutions that represent the interactions between the different objectives. Due to the complexity of MOSPs, an efficient approximation based on dynamic programming is developed. The approximation has a provable worst case performance guarantee. Even though the approximate Pareto set consists of fewer solutions, it represents a good coverage of the true set of Pareto solutions. We consider generic cost parameters that depend on the state of the system. Numerical results are presented for the time-dependent multi-objective knapsack problem, showing the value of the approximation in the special case when the state of the system is expressed in terms of time.
Original languageEnglish
Pages (from-to)1165-1175
Number of pages11
JournalComputers & Operations Research
Issue number5
Publication statusPublished - 2013


Dive into the research topics of 'Approximating multi-objective scheduling problems'. Together they form a unique fingerprint.

Cite this