Abstract
This article presents a particle swarm optimisation algorithm for solving a capacitated location routing problem (LRP). Based on the framework of particle swarm optimisation with multiple social learning terms (GLNPSO), a solution representation is designed as a multi-dimensional particle representing depot element and customer element. Each particle is decoded into a solution by using the position of a particle to determine depot location, customer assignment, and route construction. The proposed algorithm is evaluated using a set of benchmark problem instances. The results show that the solution quality is good for large problem instances and a total of nine new best solutions are found. Additional performance indices are also proposed as additional indicators to assess the operational performance of the location selection and route forming decisions.
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.
