Atiq Waliullah Siddiqui

An expected consequence approach to route choice in the maritime transportation of crude oil.

Maritime transportation is the major conduit of international trade, and the primary link for global crude oil movement. Given the volume of oil transported on international maritime links, it is not surprising that oil spills of both minor and major types result, although most of the risk-related work has been confined to the local settings. We propose an expected consequence approach for assessing oil-spill risk from intercontinental transportation of crude oil that not only adheres to the safety guidelines specified by the International Maritime Organization but also outlines a novel technique that makes use of coarse global data to estimate accident probabilities. The proposed estimation technique, together with four of the most popular cost-of-spill models from the literature, were applied to study and analyze a realistic size problem instance. Numerical analyses showed that: a shorter route may not necessarily be less risky; an understanding of the inherent oil-spill risk of different routes could potentially facilitate tanker routing decisions; and the associated negotiations over insurance premium between the transport company and the not-for-profit prevention and indemnity clubs. Finally, we note that only the linear model should be used with one of the three nonlinear cost-of-spill models for evaluating tanker routes.

Electronic supply chains

A review of electronic supply chain literature.Covered 165 papers from ISI indexed journals.Based on a five-dimensional classification scheme.Various trends and gaps identified in-terms of five dimensions. The area of e-commerce based supply chains (or e-supply chains) has received significant attention in the last two decades. Despite the high level of activity, the most recent reviews on this topic date back to the beginning of this century. In this paper, we analyzed the state of e-supply chain research published during January 2000-January 2015 AD, covering 165 articles from 47 ISI indexed journals. The analysis is performed using a five-dimensional framework comprising Topic-of-Study, Unit-of-Analysis, Research Perspective, Industry Type, and Research Method. Within these dimensions, Topic-of-Study plays a pivotal role, whereas the other four dimensions are analyzed around its sub-classification scheme. Our main objective is to establish a broader interdisciplinary understanding of the e-supply chain research domain, and to identify trends and gaps in contemporary e-supply chain theory and practice. The findings indicate that problems are addressed from different perspectives with varying levels of interest from researchers belonging to several academic disciplines including business, economics, engineering and social sciences. Our analysis also identified two distinct periods (2000-2006 and 2007 onwards) with different foci of research attention. The problems that received significant attention in the earlier period include innovation, adoption and barriers, and supply chain integration; while in the latter period, the focus seemed to have shifted towards supply chain integration and collaboration issues. Problems that received minimum interest across the two periods include customer relationship, economic and environmental impact.

A periodic planning model for maritime transportation of crude oil

Crude oil is primarily transported through sea using very large tankers. Efficient scheduling of these tankers is challenging as well as critical given long lead times, tight delivery time windows and high operational costs. We attempt to solve such a scheduling problem for an oil supplier facing supply quota and port capacity constraints. A mixed-integer programming formulation and two time-dependent solution techniques are proposed. Numerical results suggest that computing time was a function of the number, starting location, and time to availability of tankers at the supply sources. Finally, a time-based decomposition technique is presented to solve large problem instances, illustrating substantial reductions in computing time for marginally worse-off solutions.

An ontological process modelling framework for stochastic systems

Abstract Most process modelling techniques exist without any firm theoretical foundation. This results in a lack of model validation, which can be in-terms of model consistency, feasibility and goal compliance. Moreover, these techniques are mostly deterministic in nature and not applicable to stochastic systems. In this paper, we propose an ontology-based stochastic process modelling framework that further provides a specialization to failure and reliability issues. The framework is notation independent, and is primarily rooted in Bunge’s ontology. The well-established theory of reliability constructs are also mapped to facilitate the modelling of failure prone systems.

A web-based group decision support system for academic term preparation

Abstract In this paper, we present a web-based group decision support system for the Academic Term Preparation problem faced at a business school of a large Middle Eastern university. This multi-stage problem involves several stakeholders that need to coordinate for the course offerings, instructor assignments, and the preparation of the relevant timetables. This coordination is facilitated through a web application that implements all stages of the workflow. It further automates the timetabling task through an optimization module using a new multi-objective mixed integer programming model. The model is based on curriculum and student sectioning requirements; academic and administrative policies; and, the present capacity situation. The new system replaces a semi-automated spread sheet tool, resulting in improved quality of timetables, efficient workflow coordination, customized reporting, significantly reduced lead times, and eradication of human errors.

A conditional value-at-risk based methodology to intermediate-term planning of crude oil tanker fleet

Abstract Crude oil suppliers usually meet intercontinental demand through a fleet of ocean tankers, which not only have very high fixed and operating costs but also carry considerable financial risks because of the volatilities in oil demand and spot freight rate markets. Hence, most oil suppliers maintain an under-capacity fleet, and manage additional requirements through periodically adjusting a mix of various charter contracts and/or their purchase options. For this periodic fleet adjustment problem, we propose a conditional value-at-risk based methodology to hedge against extreme losses. More specifically we develop a mixed integer nonlinear programming model, where parameters are estimated via Monte-Carlo simulation, to minimize both the chartering costs and the associated financial risks. The proposed methodology was applied to a number of problem instances, generated using the marine transportation network of a major oil supplier, and it was observed that: full use of a mix of charter contracts and its purchase options significantly reduce spot charter market related risks, while substantially increase the firm or oil demand-specific risks—a key relationship driving optimal fleet decisions; and, firm-specific (tanker under-utilization) risks become increasingly irrelevant during higher oil demand periods, and that the market risks show sensitivity to the starting spot charter prices as well as the scale of delivery operations.