Abstract
The shop-scheduling problem can be simply introduced as a problem of redistribution of resources or a problem of rearrangement of operation orders. Open shop scheduling problems (OSSP) are one of the most time-consuming works in scheduling problems. In other hand Optimization techniques have obtained much attention during the past decades. Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are the most important methods used to solve optimization problems such as Open Shop Scheduling. In this paper, a hybrid optimization algorithm (IPSO) is proposed to solve Open Shop Scheduling more efficiently and accurately. Most literature referring to OSSP focuses on the optimization of one single objective.This paper offered a mathematic model for OSSP with the goal of minimizing average completion time and the number of late jobs simultaneously. The proposed method was then compared whit the results of the LINGO software and GA. The results of this comparison show that IPSO can achieve better results for the solution in a faster time. Introduction
Sign-in/Register to access full text options 
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 callDisclaimer: 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.
