Scope and Purpose – For solving combinatorial optimization problems, neural networks have traditionally been outperformed by traditional heuristic techniques developed specifically for the problem in question. This research is a step toward integrating the problem specific knowledge embedded...

It is the purpose of this paper to investigate effects of adding randomization to a memory-based heuristic. The algorithms we propose are applied to the Capacitated Minimum Spanning Tree problem (CMST), and we study the combined effects of simultaneously applying a memory-based and a...

In this paper we propose a hybrid memory adaptive heuristic for solving the Capacitated Minimum Spanning Tree (CMST) problem. We augment the problem formulation with additional non-redundant constraints via use of adaptive memory, to improve upon the performance of an elementary heuristic (the...