This paper introduces a novel practical variant, namely an open close multiple travelling salesmen problem with single depot (OCMTSP) that concerns the generalization of classical travelling salesman problem (TSP). | An open close multiple travelling salesman problem with single depot Decision Science Letters 8 2019 121 136 Contents lists available at GrowingScience Decision Science Letters homepage dsl An open close multiple travelling salesman problem with single depot Jayanth Kumar Thenepallea and Purusotham Singamsettya aVellore Institute of Technology Vellore India CHRONICLE ABSTRACT Article history This paper introduces a novel practical variant namely an open close multiple travelling Received January 16 2018 salesmen problem with single depot OCMTSP that concerns the generalization of classical Received in revised format travelling salesman problem TSP . In OCMTSP the overall salesmen can be categorized into July 10 2018 internal permanent and external outsourcing ones where all the salesmen are positioned at the Accepted August 8 2018 Available online depot city. The primary objective of this problem is to design the optimal route such that all August 12 2018 salesmen start from the depot base city and then visit a given set of cities. Each city is to be Keywords visited precisely once by exactly one salesman and only the internal salesmen have to return to Open close multiple travelling the depot city whereas the external ones need not return. To find optimal solutions an exact salesmen problem pattern recognition technique based Lexi-search algorithm LSA is developed which has been Lexi-search algorithm subjected in Matlab. Comparative computational results of the LSA have been made with the Pattern recognition technique existing methods for general multiple travelling salesman problem MTSP . Further to test the performance of LSA computational experiments have been carried out on some benchmark as well as randomly generated test instances for OCMTSP and results are reported. The overall computational results demonstrate that the proposed LSA is efficient in providing optimal and sub-optimal solutions within the considerable CPU times. 2018 .
