Covering Tour Problem (CTP) is the generalized form of Traveling Salesman Problem (TSP), which has found different applications in the designing of distribution networks, disaster relief, and transportation routing. The purpose of this problem is to determine the Hamiltoniancyclewiththe lowest costusinga subset of all the nodes, such that the other nodes would be in a distance shorter than the ...

augmented downhill simplex method (adsm) is introduced here, that is a heuristic combination of downhill simplex method (dsm) with random search algorithm. in fact, dsm is an interpretable nonlinear local optimization method. however, it is a local exploitation algorithm; so, it can be trapped in a local minimum. in contrast, random search is a global exploration, but less efficient. here, rand...

the capacitated vehicle routing problem (cvrp) is a well-known combinatorial optimization problem that holds a central place in logistics management. the vehicle routing is an applied task in the industrial transportation for which an optimal solution will lead us to better services, save more time and ultimately increase in customer satisfaction. this problem is classified into np-hard problem...

Augmented Downhill Simplex Method (ADSM) is introduced here, that is a heuristic combination of Downhill Simplex Method (DSM) with Random Search algorithm. In fact, DSM is an interpretable nonlinear local optimization method. However, it is a local exploitation algorithm; so, it can be trapped in a local minimum. In contrast, random search is a global exploration, but less efficient. Here, rand...

Real-time search methods allow an agent to perform path-finding tasks in unknown environments. Some real-time heuristic search methods may plan several elementary moves per planning step, requiring lookahead greater than inspecting inmediate successors. Recently, the propagation of heuristic changes in the same planning step has been shown beneficial for improving the performance of these metho...

A new local search heuristic, called J-Means, is proposed for solving the minimum sum-of-squares clustering problem. The neighborhood of the current solution is deened by all possible centroid-to-entity relocations followed by corresponding changes of assignments. Moves are made in such neighborhoods until a local optimum is reached. The new heuristic is compared with two other well-known local...

Researchers and practitioners frequently spend more time fine-tuning algorithms than designing and implementing them. This is particularly true when developing heuristics and metaheuristics, where the “right” choice of values for search parameters has a considerable effect on the performance of the procedure. When testing metaheuristics, performance typically is measured considering both the qu...