Abstract
Two parameter-tuned metaheuristic algorithms for the multi-level lot sizing and scheduling problem
Highlights
Lot sizing and scheduling are some of the most challenging subjects where tremendous efforts have been accomplished to propose efficient solutions
The obtained results from computational experiments show that the algorithm performs significantly better than existing algorithms like genetic algorithm (GA), simulated annealing (SA), Tabu search (TS), and
To the best of our knowledge, there is no result for employing a novel imperialist competitive algorithm (ICA) and a genetic algorithm (GA) as solution approaches for capacitated lot sizing and scheduling problem with complex setups and backlogging problems in the literature
Summary
Lot sizing and scheduling are some of the most challenging subjects where tremendous efforts have been accomplished to propose efficient solutions. Keyvanfar and Zandieh (2012) studied an economic lot scheduling problem (ELSP) and employed an ICA to provide good solutions within reasonable computational times in order to minimize setup cost, holding cost and slack cost. Lian et al (2012) investigated the optimization of process planning in which various flexibilities were considered to minimize total weighted sum of manufacturing costs They proposed an imperialist competitive algorithm to find promising solutions with reasonable computational cost. To the best of our knowledge, there is no result for employing a novel imperialist competitive algorithm (ICA) and a genetic algorithm (GA) as solution approaches for capacitated lot sizing and scheduling problem with complex setups and backlogging problems in the literature.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Industrial Engineering Computations
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
