A multi-objective analysis of a petroleum transportation network under uncertainty

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 minimizing transportation cost and minimizing product loss during transportation. The multi-objective mathematical programming (MOMP) problem is solved using the ɛ-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.