Almost all k-colorable graphs are easy to color
Journal of Algorithms
Lower bounds and reduction procedures for the bin packing problem
Discrete Applied Mathematics - Combinatorial Optimization
BISON: a fast hybrid procedure for exactly solving the one-dimensional bin packing problem
Computers and Operations Research
A robust simulated annealing based examination timetabling system
Computers and Operations Research
A grouping genetic algorithm for coloring the edges of graphs
SAC '00 Proceedings of the 2000 ACM symposium on Applied computing - Volume 1
New methods to color the vertices of a graph
Communications of the ACM
Genetic Algorithms and Grouping Problems
Genetic Algorithms and Grouping Problems
Heuristic Solution of Open Bin Packing Problems
Journal of Heuristics
Graph Coloring with Adaptive Evolutionary Algorithms
Journal of Heuristics
Journal of Heuristics
A Response to ’’On method overfitting‘‘
Journal of Heuristics
An Experimental Investigation of Iterated Local Search for Coloring Graphs
Proceedings of the Applications of Evolutionary Computing on EvoWorkshops 2002: EvoCOP, EvoIASP, EvoSTIM/EvoPLAN
Solving Equal Piles with the Grouping Genetic Algorithm
Proceedings of the 6th International Conference on Genetic Algorithms
Timetabling the Classes of an Entire University with an Evolutionary Algorithm
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
A New Genetic Local Search Algorithm for Graph Coloring
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
A Grouping Genetic Algorithm for Graph Colouring and Exam Timetabling
PATAT '00 Selected papers from the Third International Conference on Practice and Theory of Automated Timetabling III
Recent advances on two-dimensional bin packing problems
Discrete Applied Mathematics
Genetic algorithms and timetabling
Advances in evolutionary computing
RGFGA: An Efficient Representation and Crossover for Grouping Genetic Algorithms
Evolutionary Computation
Metaheuristics can solve sudoku puzzles
Journal of Heuristics
A new representation and operators for genetic algorithms applied to grouping problems
Evolutionary Computation
An improved ant colony optimisation heuristic for graph colouring
Discrete Applied Mathematics
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
No free lunch theorems for optimization
IEEE Transactions on Evolutionary Computation
Comparing evolutionary algorithms on binary constraint satisfaction problems
IEEE Transactions on Evolutionary Computation
Finding Feasible Timetables Using Group-Based Operators
IEEE Transactions on Evolutionary Computation
On the application of graph colouring techniques in round-robin sports scheduling
Computers and Operations Research
Formal analysis, hardness, and algorithms for extracting internal structure of test-based problems
Evolutionary Computation
A wide-ranging computational comparison of high-performance graph colouring algorithms
Computers and Operations Research
Towards objective measures of algorithm performance across instance space
Computers and Operations Research
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A class of problems referred to as order independent minimum grouping problems is examined and an intuitive hill-climbing method for solving such problems is proposed. Example applications of this generic method are made to two well-known problems belonging to this class: graph colouring and bin packing. Using a wide variety of different problem instance-types, these algorithms are compared to two other generic methods for this problem type: the iterated greedy algorithm and the grouping genetic algorithm. The results of these comparisons indicate that the presented applications of the hill-climbing approach are able to significantly outperform these algorithms in many cases. A number of reasons for these characteristics are given in the presented analyses.