In the last few years, the formulation of real-world optimization problems and their efficient
solution via metaheuristic algorithms has been a catalyst for a myriad of research studies. In …

The permutation flowshop problem is a classic machine scheduling problem where n jobs
must be processed on a set of m machines disposed in series and where each job must visit …

The vehicle routing problem is one of the most studied combinatorial optimization topics,
due to its practical importance and methodological interest. Yet, despite extensive …

Large manufacturing firms operate more than one production center. As a result, in relation
to scheduling problems, which factory manufactures which product is an important …

Comparing, or benchmarking, of optimization algorithms is a complicated task that involves
many subtle considerations to yield a fair and unbiased evaluation. In this paper, we …

This study develops a standardised checklist approach to improve the reporting of discrete-
event simulation, system dynamics and agent-based simulation models within the field of …

Following decades of sustained improvement, metaheuristics are one of the great success
stories of optimization research. However, in order for research in metaheuristics to avoid …

Evolutionary algorithms (EAs) have recently been suggested as a candidate for solving big
data optimization problems that involve a very large number of variables and need to be …

The design and development of metaheuristic algorithms can be time-consuming and
difficult for a number of reasons including the complexity of the problems being tackled, the …

In this paper, we advise to perform assembly line balancing simultaneously with decision-
making on parts feeding. Such integrated planning may open additional potential to reduce …