It has been shown that evolutionary algorithms are able to construct suitable search strategies for classes of Constraint Satisfaction Problems (CSPs) in Constraint Programming. This paper is an explanation of the use of multi-objective optimisation in contrast to simple additive weighting...

We consider a generalization of the classical quadratic assignment problem, where material flows between facilities are uncertain, and belong to a budgeted uncertainty set. The objective is to find a robust solution under all possible scenarios in the given uncertainty set. We present an exact...

The effectiveness and efficiency of optimization algorithms might deteriorate when solving large-scale binary integer programs (BIPs). Consequently, researchers have tried to fix the values of certain variables called adjunct variables, and only optimize a small problem version formed from the...

Automatic design of stochastic local search algorithms has been shown to be very effective in generating algorithms for the permutation flowshop problem for the most studied objectives including makespan, flowtime and total tardiness. The automatic design system uses a configuration tool to...

Many combinatorial optimization problems (COPs) encountered in real-world logistics, transportation, production, healthcare, financial, telecommunication, and computing applications are NP-hard in nature. These real-life COPs are frequently characterized by their large-scale sizes and the need...

Most metaheuristics lack a termination condition based on reasonable premises and guaranteeing the quality of the solution provided by the algorithm. We propose a methodological frame that distinguishes the concepts of properties of the final incumbent solution, rules and termination conditions....