Metaheuristic techniques have successfully contributed to the development and optimization of large-scale distributed power systems. The archived literature demonstrate that the modification or tuning of the parameters of specific metaheuristics can provide powerful tools suited for optimization of power plants with different types of constraints. In spite of the high potential of metaheuristic...

This research addresses a variant of the traveling salesman problem in drone-based delivery systems known as TSP-D. The TSP-D is combinatorial optimization which truck and drone collaborate to deliver parcels customers, with objective minimizing total time. Determining optimal solution NP-hard; thus, size problems that can be solved optimally limited. Therefore, metaheuristics are used solve pr...

Combinatorial optimisation methods are concerned with an objective function defined over an (exponentially) large search space. Often these are solved with metaheuristics, such as simulated annealing, various evolutionary strategies, tabu search, and many others. However, such metaheuristics are generally rather static creatures with relatively simple behaviours and with most intelligence deleg...

In this article we are particularly interested in packing objects defined by complex shapes encountered in logistics using Constraint Programming, Metaheuristics and non-linear inequalities.

Optimization problems are ubiquitous nowadays. Many times, their corresponding computational models necessarily leave out of consideration several characteristics and features the real world, so trying to obtain optimum solution can not be enough for a problem solving point view. The aim this paper is illustrate role metaheuristics as solutions’ generators in basic framework. Metaheuristics bec...