A comparative evaluation of heuristic line balancing techniques
Management Science
Eureka: a hybrid system for assembly line balancing
Management Science
A genetic algorithm for the job shop problem
Computers and Operations Research - Special issue on genetic algorithms
Evolution based learning in a job shop scheduling environment
Computers and Operations Research - Special issue on genetic algorithms
A fast taboo search algorithm for the job shop problem
Management Science
Exact algorithms for the guillotine strip cutting/packing problem
Computers and Operations Research
A genetic algorithm approach to cellular manufacturing systems
Computers and Industrial Engineering
An effective hybrid optimization strategy for job-shop scheduling problems
Computers and Operations Research
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
A Hybrid Genetic Algorithm for Assembly Line Balancing
Journal of Heuristics
A New Exact Algorithm for General Orthogonal D-Dimensional Knapsack Problems
ESA '97 Proceedings of the 5th Annual European Symposium on Algorithms
Parallel GRASP with path-relinking for job shop scheduling
Parallel Computing - Special issue: Parallel computing in numerical optimization
Solving Project Scheduling Problems by Minimum Cut Computations
Management Science
A Combinatorial Characterization of Higher-Dimensional Orthogonal Packing
Mathematics of Operations Research
Increasing Internet Capacity Using Local Search
Computational Optimization and Applications
An evolutionary algorithm for manufacturing cell formation
Computers and Industrial Engineering
Survivable IP network design with OSPF routing
Networks - Special Issue on Multicommodity Flows and Network Design
Computers and Operations Research
A random key based genetic algorithm for the resource constrained project scheduling problem
Computers and Operations Research
Journal of Combinatorial Optimization
Combinatorial optimization for weighing matrices with the ordering messy genetic algorithm
SEA'11 Proceedings of the 10th international conference on Experimental algorithms
BRKGA Algorithm for the Capacitated Arc Routing Problem
Electronic Notes in Theoretical Computer Science (ENTCS)
Competent genetic algorithms for weighing matrices
Journal of Combinatorial Optimization
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part II
Evolutionary algorithm for the k-interconnected multi-depot multi-traveling salesmen problem
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Hybrid approach for 2d strip packing problem using genetic algorithm
IWANN'13 Proceedings of the 12th international conference on Artificial Neural Networks: advances in computational intelligence - Volume Part I
Computers and Operations Research
Randomized heuristics for handover minimization in mobility networks
Journal of Heuristics
A black-box scatter search for optimization problems with integer variables
Journal of Global Optimization
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Random-key genetic algorithms were introduced by Bean (ORSA J. Comput. 6:154---160, 1994) for solving sequencing problems in combinatorial optimization. Since then, they have been extended to handle a wide class of combinatorial optimization problems. This paper presents a tutorial on the implementation and use of biased random-key genetic algorithms for solving combinatorial optimization problems. Biased random-key genetic algorithms are a variant of random-key genetic algorithms, where one of the parents used for mating is biased to be of higher fitness than the other parent. After introducing the basics of biased random-key genetic algorithms, the paper discusses in some detail implementation issues, illustrating the ease in which sequential and parallel heuristics based on biased random-key genetic algorithms can be developed. A survey of applications that have recently appeared in the literature is also given.