The quadratic assignment problem (QAP), one of the most difficult problems in the NP-hard
class, models many real-life problems in several areas such as facilities location, parallel …

Freight constitutes a large portion of urban daily traffic, contributing to emissions, noise, and
safety concerns. Moreover, urban freight logistics are often hindered by the last mile …

Abstract Hyper-heuristics are (meta-) heuristics that operate at a higher level to choose or
generate a set of low-level (meta-) heuristics in an attempt of solve difficult optimization …

In this paper we propose a model which aims at selecting a tight cluster from a set of points.
The same formulation applies also to the grey pattern problem where the objective is to find …

This paper studies the scheduling problem of minimising total weighted earliness and
tardiness penalties on identical parallel machines against a restrictive common due date …

Recently, genetic algorithms (GAs) and their hybrids have achieved great success in solving
difficult combinatorial optimization problems. In this paper, the issues related to the …

Freight constitutes a large portion of urban daily traffic, contributing to emissions, noise, and
safety concerns. Moreover, urban freight logistics and supply chains are often hindered by …

This paper presents a state transition based formal framework for a new search method,
called Evolutionary Ruin and Stochastic Recreate, which tries to learn and adapt to the …

This paper studies the no-wait flowshop scheduling problem with total flow time criterion,
which is NP-complete in the strong sense. A self-adaptive ruin-and-recreate (SR&R) …

Genetic and evolutionary algorithms have achieved impressive success in solving various
optimization problems. In this work, an improved genetic-evolutionary algorithm (IGEA) for …