Developing a simulated annealing algorithm for the cutting stock problem
Computers and Industrial Engineering
Fast evaluation of sequence pair in block placement by longest common subsequence computation
DATE '00 Proceedings of the conference on Design, automation and test in Europe
FAST-SP: a fast algorithm for block placement based on sequence pair
Proceedings of the 2001 Asia and South Pacific Design Automation Conference
Computers and Industrial Engineering
A New Exact Algorithm for General Orthogonal D-Dimensional Knapsack Problems
ESA '97 Proceedings of the 5th Annual European Symposium on Algorithms
An Exact Approach to the Strip-Packing Problem
INFORMS Journal on Computing
A GRASP Approach to the Container-Loading Problem
IEEE Intelligent Systems
Algorithm 864: General and robot-packable variants of the three-dimensional bin packing problem
ACM Transactions on Mathematical Software (TOMS)
INFORMS Journal on Computing
An Exact Algorithm for Higher-Dimensional Orthogonal Packing
Operations Research
VLSI module placement based on rectangle-packing by the sequence-pair
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
The two-dimensional bin packing problem with variable bin sizes and costs
Discrete Optimization
On the two-dimensional Knapsack Problem
Operations Research Letters
Evolving reusable 3d packing heuristics with genetic programming
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Maximizing revenue with allocation of multiple advertisements on a Web banner
Computers and Operations Research
Computers and Operations Research
Computers and Industrial Engineering
An efficient deterministic heuristic for two-dimensional rectangular packing
Computers and Operations Research
A global search framework for practical three-dimensional packing with variable carton orientations
Computers and Operations Research
Automating the packing heuristic design process with genetic programming
Evolutionary Computation
Data Structures for Higher-Dimensional Rectilinear Packing
INFORMS Journal on Computing
Planning in logistics: a survey
Proceedings of the 10th Performance Metrics for Intelligent Systems Workshop
Journal of Network and Computer Applications
A modified shuffled frog leaping algorithm with genetic mutation for combinatorial optimization
ICCCI'12 Proceedings of the 4th international conference on Computational Collective Intelligence: technologies and applications - Volume Part II
The generate-and-solve framework revisited: generating by simulated annealing
EvoCOP'13 Proceedings of the 13th European conference on Evolutionary Computation in Combinatorial Optimization
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The maximum profit two- or three-dimensional knapsack packing problem packs a maximum profit subset of some given rectangles or boxes into a larger rectangle or box of fixed dimensions. Items must be orthogonally packed, but no other restriction is imposed to the problem. We present a new iterative heuristic for the two-dimensional knapsack problem based on the sequence pair representation proposed by Murata et al. [VLSI module packing based on rectangle-packing by the sequence pair. IEEE Transaction on Computer Aided Design of Integrated Circuits and Systems 1996;15:1518-24] using a semi-normalized packing algorithm by Pisinger [Denser packings obtained in O(nloglogn) time. INFORMS Journal on Computing 2007;19:395-405]. Solutions are represented as a pair of sequences. In each iteration, the sequence pair is modified and transformed to a packing in order to evaluate the objective value. Simulated annealing is used to control the heuristic. A novel abstract representation of box placements, called sequence triple, is used with a similar technique for the three-dimensional knapsack problem. The heuristic is able to handle problem instances where rotation is allowed. Comprehensive computational experiments which compare the developed heuristics with previous approaches indicate very promising results for both two- and three-dimensional problems.