A Greedy Simulated Annealing-based Multiobjective Algorithm for the Minimum Weight Minimum Connected Dominating Set Problem

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The minimum connected dominating set problem is a well-known NP-hard combinatorial optimization problem in graph theory, with various fields of application including wireless sensor networks, optical networks, and systems biology. This paper presents an adaptive multiobjective simulated annealing approach to address a variant of the minimum connected dominating set problem known as the Minimum Weight Minimum Connected Dominating Set Problem. This approach combines a multiobjective Pareto set with a greedy simulated annealing algorithm to tackle the problem by simultaneously optimizing two objectives, namely the cardinality and the total weight of the connected dominating set. Experimental results compared to those obtained by current state-of-the-art approaches show the superiority of our method.

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