Hyper-heuristics have emerged as a way to raise the level of generality of search techniques
for computational search problems. This is in contrast to many approaches, which represent …

Over the past 30 years, many researchers in the field of evolutionary computation have put a
lot of effort to introduce various approaches for solving hard problems. Most of these …

Metaheuristics algorithms are designed to find approximate solutions for challenging
optimization problems. The success of the algorithm over a given optimization task relies on …

The paper introduces a novel many-objective evolutionary method, with a diversity-based
selection operator and aims to fill the “gaps” in the Pareto Front approximation and to …

This research proposes a novel indicator-based hybrid evolutionary approach that combines
approximate and exact algorithms. We apply it to a new bi-criteria formulation of the …

A travelling thief problem (TTP) is a proxy to real-life problems such as postal collection. TTP
comprises an entanglement of a travelling salesman problem (TSP) and a knapsack …

Real-world problems often consist of several interdependent subproblems. The degree of
interaction of the subproblems is associated with the complexity of the problem and solving …

Unlike other NP-hard problems, the constraints on the traveling tournament problem are so
pressing that it's hardly possible to randomly generate a valid solution, for example, to use in …

In this paper, we propose a method to solve a bi-objective variant of the well-studied
traveling thief problem (TTP). The TTP is a multi-component problem that combines two …

A plethora of combinatorial optimization problems can be linked to real-life decision
scenarios. Even nowadays, more diverse and complex problems are popping up. One of …