Solving Cutting Stock Problems via an Extended Ryan-Foster Branching Scheme and Fast Column Generation

Fuente: arXiv
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Main Authors: da Silva, Renan F. F., Schouery, Rafael C. S.
Format: Preprint
Published: 2023
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author da Silva, Renan F. F.
Schouery, Rafael C. S.
author_facet da Silva, Renan F. F.
Schouery, Rafael C. S.
contents We present a branch-cut-and-price framework to solve Cutting Stock Problems with strong relaxations using Set Covering (Packing) Formulations, which are solved by column generation. The main contributions of this paper include an extended Ryan-Foster scheme, which allows us to use this powerful branching scheme even in non-binary problems by using a conflict propagation lemma; a fast column generation process based on a diversification strategy; custom primal heuristics, enabling us to find optimal solutions for several open instances; and a technique to use a smaller feasibility tolerance in floating-point linear programming solvers, combined with numerically safe methods to produce stronger and safer lower bounds. Additional performance-improving strategies include a technique that controls the height of the branch-and-bound tree; a variable selection algorithm based on branching history; a new set of dual inequalities; insights to obtain a lean model; and the subset-row inequalities. By employing this comprehensive framework, we overcame the current state-of-the-art concerning the following problems: Cutting Stock, Skiving Stock, Ordered Open-End Bin Packing, Class-Constrained Bin Packing, and Identical Parallel Machines Scheduling with Minimum Makespan. Additionally, a new challenging benchmark for Cutting Stock is introduced.
format Preprint
id arxiv_https___arxiv_org_abs_2308_03595
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Solving Cutting Stock Problems via an Extended Ryan-Foster Branching Scheme and Fast Column Generation
da Silva, Renan F. F.
Schouery, Rafael C. S.
Optimization and Control
90C10, 90C27, 90C39, 90C57
We present a branch-cut-and-price framework to solve Cutting Stock Problems with strong relaxations using Set Covering (Packing) Formulations, which are solved by column generation. The main contributions of this paper include an extended Ryan-Foster scheme, which allows us to use this powerful branching scheme even in non-binary problems by using a conflict propagation lemma; a fast column generation process based on a diversification strategy; custom primal heuristics, enabling us to find optimal solutions for several open instances; and a technique to use a smaller feasibility tolerance in floating-point linear programming solvers, combined with numerically safe methods to produce stronger and safer lower bounds. Additional performance-improving strategies include a technique that controls the height of the branch-and-bound tree; a variable selection algorithm based on branching history; a new set of dual inequalities; insights to obtain a lean model; and the subset-row inequalities. By employing this comprehensive framework, we overcame the current state-of-the-art concerning the following problems: Cutting Stock, Skiving Stock, Ordered Open-End Bin Packing, Class-Constrained Bin Packing, and Identical Parallel Machines Scheduling with Minimum Makespan. Additionally, a new challenging benchmark for Cutting Stock is introduced.
title Solving Cutting Stock Problems via an Extended Ryan-Foster Branching Scheme and Fast Column Generation
topic Optimization and Control
90C10, 90C27, 90C39, 90C57
url https://arxiv.org/abs/2308.03595