An adaptive learning approach for no-wait flowshop scheduling problems to minimize make-span
Year: 2011
Type: article
Abstract: No-wait flowshop scheduling problem (NW-FSSP) with the objective to minimize the makespan is an important sequencing problem in the production plans and applications of no-wait flowshops can be found in several industries.In a NW-FSSP, jobs are not allowed to wait between two successive machines.The NW-FSSPs are addressed to minimize makespan and the NW-FSSP is known as a NP-Hard problem.In this study, Agarwal et al.'s 1 adaptive learning approach (ALA) is improvement for NW-FSSPs.Improvements in adaptive learning approach is similar to neural-network training.The improvement adaptive learning approach (IALA) is applied to all of the 192 problems.The proposed IALA method for NW-FSSP is compared with Aldowaisan and Allahverdi's 2 results by using Genetic heuristic.The results of computational experiments on randomly generated NW-FSSPs are show that the proposed adaptive learning approach performs quite well.
Authors: Orhan Engin, Cengiz Günaydin
Institution: Selçuk University
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,490
OpenAlex ID: W2010067528