Nature-inspired metaheuristics for multiobjective activity crashing
Many project tasks and manufacturing processes consist of interdependent time-related activities that can be represented as networks. Deciding which of these sub-processes should receive extra resources to speed up the whole network (i.e., where activity crashing should be applied) usually involves the pursuit of multiple objectives amid a lack of a priori preference information. A common decision support approach lies in first determining efficient combinations of activity crashing measures and then pursuing an interactive exploration of this space. As it is impossible to exactly solve the underlying multiobjective combinatorial optimization problem within a reasonable computation time for real-world problems, we have developed proper solution procedures based on three major (nature-inspired) metaheuristics. This paper describes these implementations, discusses their strengths, and provides results from computational experiments.
Year of publication: |
2008
|
---|---|
Authors: | Doerner, K.F. ; Gutjahr, W.J. ; Hartl, R.F. ; Strauss, C. ; Stummer, C. |
Published in: |
Omega. - Elsevier, ISSN 0305-0483. - Vol. 36.2008, 6, p. 1019-1037
|
Publisher: |
Elsevier |
Keywords: | Heuristics Multicriteria Decision making Project management |
Saved in:
Online Resource
Saved in favorites
Similar items by person
-
Doerner, K.F., (2006)
-
Pareto ant colony optimization with ILP preprocessing in multiobjective project portfolio selection
Doerner, K.F., (2006)
-
Nature-inspired metaheuristics for multiobjective activity crashing
Doerner, K.F., (2008)
- More ...