Authors: Pramesh Pudasaini; Jagat Kumar Shrestha; Rui Borges Lopes
Addresses: Department of Civil Engineering, Pulchowk Campus, Institute of Engineering, Tribhuvan University, Nepal ' Department of Civil Engineering, Pulchowk Campus, Institute of Engineering, Tribhuvan University, Nepal ' Department of Economics, Management and Industrial Engineering/CIDMA, University of Aveiro, Portugal
Abstract: In this paper, multi-objective models, based on deterministic and stochastic approaches, are proposed for the transportation subsystem of a petroleum supply chain (PSC) network in Nepal. Demand has been considered the uncertain parameter for two-stage stochastic analysis using scenario tree generation. The models, designed for multiple sources, destinations and products, have the objectives of minimising transportation cost and minimising product loss during transportation. The multi-objective mathematical programming (MOMP) problem is solved using the ε-constraint method. Comparison of deterministic and stochastic approaches is drawn to make the decision maker (DM) aware of the effects of demand uncertainty. The analysis and computational results provide the DM with a decision support tool for planning the optimal shipping pattern under different scenarios of time-varying product demands.
Keywords: multi-objective optimisation; petroleum transportation; demand uncertainty; scenario analysis.
International Journal of Logistics Systems and Management, 2021 Vol.40 No.3, pp.377 - 395
Received: 29 Jun 2019
Accepted: 13 Oct 2019
Published online: 11 Jan 2022 *