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Bin packing and cutting stock problems: Mathematical models and exact algorithms
We review the most important mathematical models and algorithms developed for the exact
solution of the one-dimensional bin packing and cutting stock problems, and experimentally …
solution of the one-dimensional bin packing and cutting stock problems, and experimentally …
[KNYGA][B] Hyper-heuristics: theory and applications
Hyper-heuristics is a fairly recent technique that aims at effectively solving various real-world
optimization problems. This is the first book on hyper-heuristics, and aims to bring together …
optimization problems. This is the first book on hyper-heuristics, and aims to bring together …
Genetic programming for dynamic workflow scheduling in fog computing
A lifelong learning hyper-heuristic method for bin packing
We describe a novel hyper-heuristic system that continuously learns over time to solve a
combinatorial optimisation problem. The system continuously generates new heuristics and …
combinatorial optimisation problem. The system continuously generates new heuristics and …
A unified hyper-heuristic framework for solving bin packing problems
One-and two-dimensional packing and cutting problems occur in many commercial contexts,
and it is often important to be able to get good-quality solutions quickly. Fairly simple …
and it is often important to be able to get good-quality solutions quickly. Fairly simple …
Learning ensembles of priority rules for online scheduling by hybrid evolutionary algorithms
This paper studies the computation of ensembles of priority rules for the One Machine
Scheduling Problem with variable capacity and total tardiness minimization. Concretely, we …
Scheduling Problem with variable capacity and total tardiness minimization. Concretely, we …
Dual inequalities for stabilized column generation revisited
Column generation (CG) models have several advantages over compact formulations: they
provide better linear program bounds, may eliminate symmetry, and can hide nonlinearities …
provide better linear program bounds, may eliminate symmetry, and can hide nonlinearities …
Qal-bp: an augmented lagrangian quantum approach for bin packing
The bin packing is a well-known NP-Hard problem in the domain of artificial intelligence,
posing significant challenges in finding efficient solutions. Conversely, recent advancements …
posing significant challenges in finding efficient solutions. Conversely, recent advancements …
Assessing hyper-heuristic performance
Limited attention has been paid to assessing the generality performance of hyper-heuristics.
The performance of hyper-heuristics has been predominately assessed in terms of optimality …
The performance of hyper-heuristics has been predominately assessed in terms of optimality …