Study of different setup costs in SingleGA to solve a one-dimensional cutting stock problem

Abstract

This paper presents the application of new costs for one recent approach, called SingleGA, in solving One-Dimensional cutting stock problem. The cutting problem basically consists in finding the best way to obtain parts of distinct sizes (items) from the cutting of larger parts (objects) with the purpose of minimizing a specific cost or maximizing the profit. The obtained results of SingleGA are compared to the following methods: SHP, Kombi234, ANLCP300 and Symbio, found in literature, verifying its capacity to find feasible and competitive solutions. The computational results show that variations of SingleGA posses good results, improving as setup cost increases.

Column Generation Model in Capacitated Multi-Periods Cutting Stock Problem with Pattern Set-Up Cost

“…There has been a lot of researches on CSP, which started from one-dimensional CSP (Brandão et al (2018); Arbib et al (2016); Garra a et al (2016) ; Rodrigo and Shashikala (2017)). Rodrigo et al (2012) proposed the pattern generation algorithm to determine patterns in two-dimensional CSP with location constraints.…”

Set Covering Model in Solving Multiple Cutting Stock Problem

“…CGT was a method that can provide the best solution in completing linear programs, because of the approach to solve large-scale linear program problems. Some of the researches about PG and CGT have been done ((Brandão et al, 2018;Mellouli and Dammak, 2008;Ma et al, 2018;Octarina et al, 2019). Gilmore and Gomory model also can be developed into different formulations using the set covering model.…”