Um algoritmo exato com ordenamento parcial para solução de um problema de programação da produção: experimentos computacionais

Yanasse, Horácio Hideki; Becceneri, José Carlos; Soma, Nei Yoshihiro

doi:10.1590/s0104-530x2007000200012

Cited by 5 publications

(1 citation statement)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Yanasse et al. () proposed exact and heuristic methods using properties of the solution of MOSP to establish partial orders in which the nodes in the graph should be closed. An adaptive GA for large‐sized open stack problems is presented in De Giovanni et al.…”

Section: Introductionmentioning

confidence: 99%

A biased random‐key genetic algorithm for the minimization of open stacks problem

Gonçalves

Resende

Costa

2014

Int Trans Operational Res

View full text Add to dashboard Cite

This paper describes a biased random-key genetic algorithm (BRKGA) for the minimization of the open stacks problem (MOSP). The MOSP arises in a production system scenario, and consists of determining a sequence of cutting patterns that minimize the maximum number of open stacks during the cutting process. The proposed approach combines a BRKGA and a local search procedure for generating the sequence of cutting patterns. A novel fitness function for evaluating the quality of the solutions is also developed. Computational tests are presented using available instances taken from the literature. The high quality of the solutions obtained validate the proposed approach.

show abstract

Section: Introductionmentioning

confidence: 99%

A biased random‐key genetic algorithm for the minimization of open stacks problem

Gonçalves

Resende

Costa

2014

Int Trans Operational Res

View full text Add to dashboard Cite

show abstract

The minimization of open stacks problem: A review of some properties and their use in pre-processing operations

Yanasse

Senne

2010

European Journal of Operational Research

View full text Add to dashboard Cite

A review of three decades of research on some combinatorial optimization problems

Yanasse

2013

Pesqui. Oper.

Self Cite

View full text Add to dashboard Cite

ABSTRACT. This paper presents an overview of our research in combinatorial optimization problems. Over the last three decades, our team has been studying mostly optimization problems that arise in industrial environments through the elaboration and solution of mathematical decision models. In addition to elaborating innovative models, we have improved upon existing solutions to complex problems, helping decision makers and researchers to better understand complex industrial systems. Our work has focused on the development of computationally more efficient algorithms that improve on existing methods by improving the solution quality or reducing the computation effort to obtain good solutions. While some of our earlier work became less necessary with the speed up of the computational facilities, the search for improved solution quality and reduced computational effort continues. After reviewing our findings on lot sizing, production scheduling, cutting problems, pattern sequencing, tool switches in flexible manufacturing machines and integrated cutting and sequencing problems, we propose topics for future study.

show abstract

Um algoritmo exato com ordenamento parcial para solução de um problema de programação da produção: experimentos computacionais

Cited by 5 publications

References 10 publications

A biased random‐key genetic algorithm for the minimization of open stacks problem

A biased random‐key genetic algorithm for the minimization of open stacks problem

The minimization of open stacks problem: A review of some properties and their use in pre-processing operations

A review of three decades of research on some combinatorial optimization problems

Contact Info

Product

Resources

About