Routing problems, such as the traveling salesman problem and the vehicle routing problem,
are widely studied both because of their classic academic appeal and their numerous real …

Randomized search heuristics such as evolutionary algorithms, genetic algorithms,
evolution strategies, ant colony and particle swarm optimization turn out to be highly …

There has been a recent surge of success in optimizing deep reinforcement learning (DRL)
models with neural evolutionary algorithms. This type of method is inspired by biological …

The traveling salesman problem (TSP) is a challenging problem in combinatorial
optimization. In this paper we consider the multiobjective TSP for which the aim is to obtain …

Most multiobjective evolutionary algorithms are based on Pareto dominance for measuring
the quality of solutions during their search, among them NSGA-II is well-known. A very few …

List of References on Evolutionary Multiobjective Optimization Page 1 List of References on
Evolutionary Multiobjective Optimization Carlos A. Coello Coello ccoello@cs.cinvestav.mx …

Many real world optimization problems are time-dependent and some of them can be
modeled by the dynamic TSPs (DTSPs). A DTSP is harder than a general TSP, which is a …

Multiobjective evolutionary algorithms have already been used for the optimization of the
processing conditions of a co‐rotating twin screw extruder. In the present paper, we develop …

Traveling Salesperson Problem (TSP) is among the most-studied and hard combinatorial
optimization problems and has been investigated by numerous researchers of both …

The traveling salesman problem (TSP) is a well known NP-hard benchmark problem for
discrete optimization. However, there is a lack of TSP test instances for multiobjective …