When evaluating algorithms a very important goal is to perform better than the state-of-the-art techniques.. This requires experimental tests to compare the new algorithm with respect to the rest. It is, in general, hard to make fair comparisons between algorithms such as metaheuristics. The reason is that we can infer di erent conclusions from the same results depending on the metrics we use a...

Heuristic and metaheuristic techniques are used for solving computationally hard optimization problems. Local search is a heuristic technique while Ant colony optimization (ACO), inspired by the ants’ foraging behavior, is one of the most recent metaheuristic technique. These techniques are used for solving optimization problems. Multiple-Input Multiple-Output (MIMO) detection problem is an NP-...

We present a metaheuristic methodology for the Capacitated Vehicle Routing Problem with two-dimensional loading constraints (2LCVRP). 2L-CVRP is a generalisation of the Capacitated Vehicle Routing Problem, in which customer demand is formed by a set of twodimensional, rectangular, weighted items. The purpose of this problem is to produce the minimum cost routes, starting and terminating at a ce...