Discrete optimization
Simulated annealing and Boltzmann machines: a stochastic approach to combinatorial optimization and neural computing
A fast algorithm for coloring Meyniel graphs
Journal of Combinatorial Theory Series B
Solving the maximum clique problem using a tabu search approach
Annals of Operations Research - Special issue on Tabu search
Multilevel k-way partitioning scheme for irregular graphs
Journal of Parallel and Distributed Computing
Algorithm 457: finding all cliques of an undirected graph
Communications of the ACM
A Hybrid Genetic Algorithm for the Maximum Clique Problem
Proceedings of the 6th International Conference on Genetic Algorithms
A fast algorithm for the maximum clique problem
Discrete Applied Mathematics - Sixth Twente Workshop on Graphs and Combinatorial Optimization
A branch-and-cut algorithm for the pallet loading problem
Computers and Operations Research
Some experiments with a simple tabu search algorithm for the manufacturer's pallet loading problem
Computers and Operations Research
Computers and Operations Research
Computers and Operations Research
A decomposition approach for the probabilistic maximal covering location-allocation problem
Computers and Operations Research
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We consider in this paper a new lagrangean relaxation with clusters for the Manufacturer's Pallet Loading Problem (MPLP). The relaxation is based on the MPLP formulated as a Maximum Independent Set Problem (MISP) and represented in a conflict graph that can be partitioned in clusters. The edges inter clusters are relaxed in a lagrangean fashion. Computational tests attain the optimality for some instances considered difficult for a lagrangean relaxation. Our results show that this relaxation can be a successful approach for hard combinatorial problems modeled in conflict graphs. Moreover, we propose a column generation approach for the MPLP derived from the idea behind the lagrangean relaxation proposed.