Abstract
This work presents a Semi Adaptive Large Neighborhood Search (SALNS) for the Maintenance Scheduling and Routing Problem. A new removal method based on the behavior of risk in maintenance is proposed. It is combined with several destroy and repair operators. A semi adaptive mechanism that ensures effective mix between diversification and learning is proposed. We conduct a comparative analysis with the solver and with adapted algorithms schemes from the literature: classical ALNS and ALNS with learning automata (LA-ALNS). All the algorithms consider the same choices related to problem’s specifications and use the same local search procedure. The proposed metaheuristic chooses the most suitable heuristics while alternating between learning and diversification to obtain high quality solutions.
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.
