Simulated Annealing: use of new tool in bin packing
Annals of Operations Research
The hardest constraint problems: a double phase transition
Artificial Intelligence
Approximation algorithms for bin packing: a survey
Approximation algorithms for NP-hard problems
Genetic Algorithms and Grouping Problems
Genetic Algorithms and Grouping Problems
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Heuristic Solution of Open Bin Packing Problems
Journal of Heuristics
Journal of Heuristics
A Response to ’’On method overfitting‘‘
Journal of Heuristics
New TSP Construction Heuristics and Their Relationshipsto the 2-Opt
Journal of Heuristics
An Approximation Scheme for Bin Packing with Conflicts
SWAT '98 Proceedings of the 6th Scandinavian Workshop on Algorithm Theory
Recent Metaheuristic Algorithms for the Generalized Assignment Problem
ICKS '04 Proceedings of the International Conference on Informatics Research for Development of Knowledge Society Infrastructure
A genetic algorithm for the freight consolidation problem with one-dimensional container loading
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Energy efficient spatial TDMA scheduling in wireless networks
Computers and Operations Research
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The tradeoff between the speed and quality of the solutions obtained by various construction and local search algorithms for the elementary bin packing problem (BPP) are analyzed to obtain useful information for designing algorithms for real-world problems that can be modeled as BPPs. On the basis of intensive computational experiments, we observe that the framework of a solution (i.e., a part of a solution consisting of large items or items with tight constraints) should be constructed in the early stages of a local search. New local search algorithms are proposed as empirical support for the observation.