Multi-constructor CMSA for the maximum disjoint dominating sets problem

We propose the Multi-Constructor CMSA, a Construct, Merge, Solve and Adapt (CMSA) algorithm that employs multiple heuristic procedures, respectively solution constructors, for the Maximum Disjoint Dominating Sets Problem (MDDSP). At every iteration of the search procedure, the solution components built by the constructors are merged into a sub-instance, which is subsequently solved by an exact solver and then adapted to keep only beneficial solution components. In our CMSA the solution constructors are chosen at random according to their relative probabilities, which are adapted during the search, through a mechanism based on reinforcement learning. We test two variants of the new Multi-Constructor CMSA that employ, respectively, two and six solution constructors, on a new set of 3600 problem instances, encompassing random graphs, Watts–Strogatz networks and Barabási-Albert networks, generated through a Hammersley sampling procedure on the instance space. We compare our algorithm against six heuristics from the literature, as well as with the standard version of CMSA. Furthermore, we employ an integer linear programming (ILP) model that is able to achieve a good performance for small, sparse graphs. Overall, the experimental results show that all versions of CMSA outperform by a large margin the previous state of the art and that, among the variants of CMSA, the novel version that combines two constructors provides slightly better results than the other ones, more prominently on larger graphs

The weighted independent domination problem: ILP model and algorithmic approaches

This work deals with the so-called weighted independent domination problem, which is an N P -hard combinatorial optimization problem in graphs. In contrast to previous theoretical work from the liter- ature, this paper considers the problem from an algorithmic perspective. The first contribution consists in the development of an integer linear programming model and a heuristic that makes use of this model. Sec- ond, two greedy heuristics are proposed. Finally, the last contribution is a population-based iterated greedy algorithm that takes profit from the better one of the two developed greedy heuristics. The results of the compared algorithmic approaches show that small problem instances based on random graphs are best solved by an efficient integer linear programming solver such as CPLEX. Larger problem instances are best tackled by the population-based iterated greedy algorithm. The experimental evaluation considers random graphs of different sizes, densities, and ways of generating the node and edge weights

The Weighted Independent Domination Problem: ILP Model and Algorithmic Approaches

This work deals with the so-called weighted independent domination problem, which is an $NP$-hard combinatorial optimization problem in graphs. In contrast to previous work, this paper considers the problem from a non-theoretical perspective. The first contribution consists in the development of three integer linear programming models. Second, two greedy heuristics are proposed. Finally, the last contribution is a population-based iterated greedy metaheuristic which is applied in two different ways: (1) the metaheuristic is applied directly to each problem instance, and (2) the metaheuristic is applied at each iteration of a higher-level framework---known as construct, merge, solve \& adapt---to sub-instances of the tackled problem instances. The results of the considered algorithmic approaches show that integer linear programming approaches can only compete with the developed metaheuristics in the context of graphs with up to 100 nodes. When larger graphs are concerned, the application of the populated-based iterated greedy algorithm within the higher-level framework works generally best. The experimental evaluation considers graphs of different types, sizes, densities, and ways of generating the node and edge weights

Bond graph based multiphysic modelling of anion exchange membrane water electrolysis cell

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this recordThis work is an attempt to develop and validate a graphical dynamical model of an AEM electrolysis cell based on Bond Graphs, an energy based tool that allows to represent multiphysics systems. The model of the cell lays a foundation for developing a complete representation for AEM electrolysers which can be used for simulation as well as for developing control algorithms and fault diagnosis. Parameter identification and model validation is achieved using experimental data.European Commissio