Vehicle routing and capacity planning : A three-phase algorithm. Issue 8 (17th November 2021)

• Record Type: Journal Article
• Authors: Dhurkari, Ram Kumar; Swain, Anjan Kumar; Patjoshi, Sanjeeb Kumar
• Is Part Of: Journal of information & optimization sciences. Volume 42:Issue 8(2021)
• Page Start: 1923
• Page End: 1942
• Publication Date: 2021-11-17
• Subjects: 14C05 -- 14C25 -- 14C15; Regular rings -- Von-neumann regular elements -- Von-neumann regular rings -- Vehicle routing -- Capacity planning -- Decision support system -- Heuristics -- Demand splitting; Electronic data processing -- Periodicals; Information science -- Periodicals; Mathematical optimization -- Periodicals; 519.6
• DOI: 10.1080/02522667.2021.1968576
• Languages: English
• ISSNs: 0252-2667

Abstract

Abstract: In this paper, a three-phase algorithm is designed for solving a real problem of vehicle capacity and route optimization. The proposed algorithm fulfills non-stochastic demand in a limited time window by optimally allocating vehicles of heterogeneous capacity. The pricing model of the supplier (CMMF- a popular Co-operative Milk Marketing Federation of southern India) to transport fodder from the central production facility to different destinations was not very encouraging for the vehicle owners. In CMMF's pricing model, it is not possible to reduce the cost of transportation by vehicle capacity optimization or route optimization. CMMF was using the manual system of assignment of the vehicle to different demand locations often resulting in vehicles traveling longer distances with unused capacity. Management saw an opportunity to optimally load vehicles and fulfill various demand locations in such a way that the vehicle travels minimum distance with unused capacity. The proposed algorithm is tested on a sample 100 node network with actual demands and relevant data like demand arrival date, a connected network of demand locations, distance of demand locations from the source, and list of vehicles that are used in the existing system. A decision support system is developed to prescribe solutions to the decision-maker with different threshold unused capacity (5%, 10%, 15%, and 20%) of vehicles. Subject to the imposed constraints, a considerable reduction in the unused capacity (Kilogram-Kilometer) of vehicles is recorded.