Journal of Parallel and Distributed Computing
Using a tabu search approach for solving the two-dimensional irregular cutting problem
Annals of Operations Research - Special issue on Tabu search
Best-first search methods for constrained two-dimensional cutting stock problems
Operations Research
Approximation schemes for covering and packing problems in image processing and VLSI
Journal of the ACM (JACM)
Computers and Operations Research
Exact algorithms for the guillotine strip cutting/packing problem
Computers and Operations Research
A genetic algorithm for a 2D industrial packing problem
Computers and Industrial Engineering
A Review of the Application ofMeta-Heuristic Algorithms to 2D Strip Packing Problems
Artificial Intelligence Review
Computers and Industrial Engineering
Bin Packing with Adaptive Search
Proceedings of the 1st International Conference on Genetic Algorithms
An Exact Approach to the Strip-Packing Problem
INFORMS Journal on Computing
A new heuristic recursive algorithm for the strip rectangular packing problem
Computers and Operations Research
A New Placement Heuristic for the Orthogonal Stock-Cutting Problem
Operations Research
Reactive GRASP for the strip-packing problem
Computers and Operations Research
A recursive branch-and-bound algorithm for the rectangular guillotine strip packing problem
Computers and Operations Research
A Simulated Annealing Enhancement of the Best-Fit Heuristic for the Orthogonal Stock-Cutting Problem
INFORMS Journal on Computing
Grid branch-and-bound for permutation flowshop
PPAM'11 Proceedings of the 9th international conference on Parallel Processing and Applied Mathematics - Volume Part II
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This paper presents a parallel branch-and-bound method to address the two-dimensional rectangular guillotine strip cutting problem. Our paper focuses on a parallel branching schema. We present a series of computational experiments to evaluate the strength of the approach. Optimal solutions have been found for some benchmark instances that had unknown solutions until now. For many other instances, we demonstrate that the proposed approach is time effective. The efficiency of the parallel version of the algorithm is compared and the speedup, when increasing the number of processors, is clearly demonstrated with an upper bound calculated by a specialised heuristic procedure.