Integrated planning of downstream petroleum supply chain: A multi-objective stochastic approach

In studying petroleum supply chain networks, past studies have largely segregated three critical decision-making aspects: integrated planning, uncertainties, and multi-objective setting. This study focuses on consolidating these aspects and proposes a stochastic, multi-objective, mixed-integer linear programming model for strategic and tactical planning of downstream petroleum supply chain (DPSC) networks. Demand, considered the uncertain parameter, is modeled using a two-stage stochastic approach based on scenarios. The model-designed for multiple supply centers, distribution centers, products, and transportation modes-also considers transshipment between the centers. The objective functions consider simultaneous minimization of transportation cost and product loss cost that is incurred during transportation between the centers. The application of the proposed model is demonstrated with a case study of a real-world DPSC network undergoing construction of new pipelines and expansion of storage facilities. The augmented -constraint method is used to solve the model. Interesting trade-offs in the case study are analyzed, aiding the decision-makers in exploiting the model as a decision-support tool to better understand the complexity, flexibility, and risk of integrated decision-making under uncertainty

Rural road network performance and pre-disaster planning: an assessment methodology considering redundancy

This paper introduces a new methodology to evaluate the performance of rural road networks when a link in the network is disrupted due to events such as natural disasters, accidents, and maintenance closures. As a measure of network resilience, we propose a simpler approach to quantify redundancy by introducing two indices that link the concept of road network redundancy with the increase in travel distance of the overall network when a road link fails. We apply the problem formulation to a real-world rural road network which was heavily affected by the 2015 Gorkha Earthquake in Nepal. Based on the results from our analyses, we found these indices easy to use, pragmatic, and reliable for the case under study. With the proposed tool, decision-makers can predict and monitor the performance of rural road networks for pre-disaster (or predisruption) planning, thereby ensuring the smooth connectivity for goods and services during emergencies

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

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.publishe