Biased random-key genetic algorithms: A review
This paper is a comprehensive literature review of Biased Random-Key Genetic Algorithms
(BRKGA). BRKGA is a metaheuristic that employs random-key-based chromosomes with …
(BRKGA). BRKGA is a metaheuristic that employs random-key-based chromosomes with …
A multistart biased random key genetic algorithm for the flexible job shop scheduling problem with transportation
SM Homayouni, DBMM Fontes… - International …, 2023 - Wiley Online Library
This work addresses the flexible job shop scheduling problem with transportation (FJSPT),
which can be seen as an extension of both the flexible job shop scheduling problem (FJSP) …
which can be seen as an extension of both the flexible job shop scheduling problem (FJSP) …
A novel hybrid fuzzy–metaheuristic approach for multimodal single and multi-objective optimization problems
F Keivanian, R Chiong - Expert Systems with Applications, 2022 - Elsevier
In this paper, we propose a novel hybrid fuzzy–metaheuristic approach with the aim of
overcoming premature convergence when solving multimodal single and multi-objective …
overcoming premature convergence when solving multimodal single and multi-objective …
[PDF][PDF] Random-key genetic algorithms
JF Gonçalves, MGC Resende - Handbook of heuristics, 2018 - drive.google.com
A random-key genetic algorithm is an evolutionary metaheuristic for discrete and global
optimization. Each solution is encoded as a vector of n random keys, where a random key is …
optimization. Each solution is encoded as a vector of n random keys, where a random key is …
A bi-objective multi-population biased random key genetic algorithm for joint scheduling quay cranes and speed adjustable vehicles in container terminals
DBMM Fontes, SM Homayouni - Flexible Services and Manufacturing …, 2023 - Springer
This work formulates a mixed-integer linear programming (MILP) model and proposes a bi-
objective multi-population biased random key genetic algorithm (mp-BRKGA) for the joint …
objective multi-population biased random key genetic algorithm (mp-BRKGA) for the joint …
An exact solution method and a genetic algorithm-based approach for the unit commitment problem in conventional power generation systems
The unit commitment problem (UCP) is one of the fundamental problems in power systems
planning and operations that comprises two decisions: commitment and dispatching of …
planning and operations that comprises two decisions: commitment and dispatching of …
Hybrid method with CS and BRKGA applied to the minimization of tool switches problem
The minimization of tool switches problem (MTSP) seeks a sequence to process a set of jobs
so that the number of tool switches required is minimized. The MTSP is well known to be NP …
so that the number of tool switches required is minimized. The MTSP is well known to be NP …
Polynomial time algorithms and extended formulations for unit commitment problems
Recently, increasing penetration of renewable energy generation has created challenges for
power system operators to perform efficient power generation daily scheduling, due to the …
power system operators to perform efficient power generation daily scheduling, due to the …
A biased random key genetic algorithm applied to the electric distribution network reconfiguration problem
H De Faria, MGC Resende, D Ernst - Journal of Heuristics, 2017 - Springer
This work presents a biased random-key genetic algorithm (BRKGA) to solve the electric
distribution network reconfiguration problem (DNR). The DNR is one of the most studied …
distribution network reconfiguration problem (DNR). The DNR is one of the most studied …
Survey on applications of biased-random key genetic algorithms for solving optimization problems
This paper presents a survey on studies devising biased-random key genetic algorithms
(BRKGAs), a novel variant of the ordinary genetic algorithms (GAs) introduced in 2000s, for …
(BRKGAs), a novel variant of the ordinary genetic algorithms (GAs) introduced in 2000s, for …