Variable objective search

Authors:
Sergiy Butenko;Oleksandra Yezerska;Balabhaskar Balasundaram
Affiliations:
Industrial and Systems Engineering, Texas A&M University, College Station, USA 77843-3131;Industrial and Systems Engineering, Texas A&M University, College Station, USA 77843-3131;Industrial Engineering & Management, Oklahoma State University, Stillwater, USA 74078
Venue:
Journal of Heuristics
Year:
2013

Citing 3
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Abstract

This paper introduces the variable objective search framework for combinatorial optimization. The method utilizes different objective functions used in alternative mathematical programming formulations of the same combinatorial optimization problem in an attempt to improve the solutions obtained using each of these formulations individually. The proposed technique is illustrated using alternative quadratic unconstrained binary formulations of the classical maximum independent set problem in graphs.