A dynamic multiarmed bandit-gene expression programming hyper-heuristic for combinatorial optimization problems [PDF]
, 2015 Hyper-heuristics are search methodologies that aim to provide high-quality solutions across a wide variety of problem domains, rather than developing tailor-made methodologies for each problem instance/domain.
Graham Kendall +5 more
core +4 more sources
What Makes a Transformer Solve the TSP? A Component-Wise Analysis
MathematicsThe Traveling Salesman Problem (TSP) remains a central benchmark in combinatorial optimization, with applications in logistics, manufacturing, and network design.
Ignacio Araya +4 more
doaj +1 more source
An experimental study of hyper-heuristic selection and acceptance mechanism for combinatorial t-way test suite generation [PDF]
, 2017 Recently, many meta-heuristic algorithms have been proposed to serve as the basis of a t -way test generation strategy (where t indicates the interaction strength) including Genetic Algorithms (GA), Ant Colony Optimization (ACO), Simulated Annealing (SA),
Ahmed, Bestoun S. +3 more
core +3 more sources
The Scientific Landscape of Hyper-Heuristics: A Bibliometric Analysis Based on Scopus
AlgorithmsHyper-heuristics emerged as a broader metaheuristic framework to address the limitations of traditional optimization heuristics. By abstracting the design of low-level heuristics, hyper-heuristics offer a flexible and adaptable approach to solving ...
Helen C. Peñate-Rodríguez +3 more
doaj +1 more source
Tailoring hyper-heuristics to specific instances of a scheduling problem using affinity and competence functions [PDF]
, 2014 Hyper-heuristics are high level heuristics which coordinate lower level ones to solve a given problem. Low level heuristics, however, are not all as competent/good as each other at solving the given problem and some do not work together as well as others.
Abdellah Salhi +17 more
core +1 more source
Automated generation of dispatching rules for the green unrelated machines scheduling problem
Complex & Intelligent SystemsThe concept of green scheduling, which deals with the environmental impact of the scheduling process, is becoming increasingly important due to growing environmental concerns.
Nikolina Frid +2 more
doaj +1 more source
Evolving team compositions by agent swapping [PDF]
, 2012 Optimizing collective behavior in multiagent systems requires algorithms to find not only appropriate individual behaviors but also a suitable composition of agents within a team.
Floreano, D. +3 more
core +2 more sources
Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions [PDF]
, 2014 Copyright © 2014 Elsevier. NOTICE: this is the author’s version of a work that was accepted for publication in Environmental Modelling and Software. Changes resulting from the publishing process, such as peer review, editing, corrections, structural ...
Barbour, E.J. +21 more
core +1 more source
A comparative study of fuzzy parameter control in a general purpose local search metaheuristic [PDF]
, 2016 There is a growing number of studies on general purpose metaheuristics that are directly applicable to multiple domains. Parameter setting is a particular issue considering that many of such search methods come with a set of ...
Jackson, Warren G. +2 more
core +1 more source
Exact/Heuristic Hybrids Using rVNS and Hyperheuristics for Workforce Scheduling [PDF]
, 2007 In this paper we study a complex real-world workforce scheduling problem. We propose a method of splitting the problem into smaller parts and solving each part using exhaustive search. These smaller parts comprise a combination of choosing a method to select a task to be scheduled and a method to allocate resources, including time, to the selected task.
Remde, Stephen M. +3 more
openaire +2 more sources