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- W3147007906 abstract "The dynamic weapon-target assignment (DWTA) problem is an important issue in the field of military command and control. An asset-based DWTA optimization model was proposed with four kinds of constraints considered, including capability constraints, strategy constraints, resource constraints and engagement feasibility constraints. A general virtual representation of decisions was presented to facilitate the generation of feasible decisions. The representation is in essence the permutation of all assignment pairs. A construction procedure converts the permutations into real feasible decisions. In order to solve this problem, three evolutionary decision-making algorithms, including a genetic algorithm and two memetic algorithms, were developed. Experimental results show that the memetic algorithm based on greedy local search can generate obviously better DWTA decisions, especially for large-scale problems, than the genetic algorithm and the memetic algorithm based on steepest local search." @default.
- W3147007906 created "2021-04-13" @default.
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- W3147007906 date "2009-01-01" @default.
- W3147007906 modified "2023-09-28" @default.
- W3147007906 title "Evolutionary decision-makings for the dynamic weapon-target assignment problem" @default.
- W3147007906 hasPublicationYear "2009" @default.
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