A tutorial on the design, experimentation and application of metaheuristic algorithms to real-world optimization problems
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 …
solution via metaheuristic algorithms has been a catalyst for a myriad of research studies. In …
A new vision of approximate methods for the permutation flowshop to minimise makespan: State-of-the-art and computational evaluation
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 …
must be processed on a set of m machines disposed in series and where each job must visit …
Hybrid genetic search for the CVRP: Open-source implementation and SWAP* neighborhood
T Vidal - Computers & Operations Research, 2022 - Elsevier
The vehicle routing problem is one of the most studied combinatorial optimization topics,
due to its practical importance and methodological interest. Yet, despite extensive …
due to its practical importance and methodological interest. Yet, despite extensive …
Iterated Greedy methods for the distributed permutation flowshop scheduling problem
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 …
to scheduling problems, which factory manufactures which product is an important …
Best practices for comparing optimization algorithms
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 …
many subtle considerations to yield a fair and unbiased evaluation. In this paper, we …
Strengthening the reporting of empirical simulation studies: Introducing the STRESS guidelines
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 …
event simulation, system dynamics and agent-based simulation models within the field of …
[HTML][HTML] Metaheuristics “in the large”
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 …
stories of optimization research. However, in order for research in metaheuristics to avoid …
Heterogeneous cooperative co-evolution memetic differential evolution algorithm for big data optimization problems
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 …
data optimization problems that involve a very large number of variables and need to be …
Automated design of metaheuristic algorithms
T Stützle, M López-Ibáñez - Handbook of metaheuristics, 2019 - Springer
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 …
difficult for a number of reasons including the complexity of the problems being tackled, the …
Preventing ergonomic risks with integrated planning on assembly line balancing and parts feeding
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 …
making on parts feeding. Such integrated planning may open additional potential to reduce …