Jin-Hwa Song

A maritime inventory routing problem: Practical approach

Despite of the practicality of the motivation of the inventory routing problem (IRP), there are few successful implementation stories of IRP based decision support systems which utilize optimization algorithms. Besides the fact that the IRP is an extremely challenging optimization problem, simplifications and assumptions made in the definition of typical IRP in the literature make it even more difficult to take advantage of the developed technologies for IRP in practice. This paper introduces a flexible modeling framework for IRP, which can accommodate various practical features. A simple algorithmic framework of an optimization based heuristic method is also proposed. A case study on a practical maritime inventory routing problem (MIRP) shows that the proposed modeling and algorithmic framework is flexible and effective enough to be a choice of model and solution method for practical inventory routing problems.

A Branch-Price-and-Cut Algorithm for Single-Product Maritime Inventory Routing

A branch-price-and-cut algorithm is developed for a complex maritime inventory-routing problem with varying storage capacities and production/consumption rates at facilities. The resulting mixed-integer pricing problem is solved exactly and efficiently using a dynamic program that exploits certain “extremal” characteristics of the pricing problem. The formulation is tightened by using the problems boundary conditions in preprocessing and to restrict the set of columns that are produced by the pricing problem. Branching schemes and cuts are introduced that can be implemented efficiently and that preserve the structure of the pricing problem. Some of the cuts are inspired by the capacity cuts known for the vehicle-routing problem, whereas others specifically target fractional solutions brought about by individual vessels “competing” for limited inventory at load ports and limited storage capacity at discharge ports. The branch-price-and-cut approach solves practically sized problems motivated by the operations of an oil company to optimality, and it provides reasonable bounds for larger instances.

Feedstock Routing in the ExxonMobil Downstream Sector

ExxonMobil annually transports significant volumes of vacuum gas oil (VGO) from supply points in Europe to refineries in the United States. Optimizing these transportation costs by using modern mathematical programming technology can provide significant cost savings. We developed a mixed-integer programming formulation for VGO routing and inventory management, and we integrated it into a decision support tool to enable experienced traders and schedulers to further improve the performance of ExxonMobils downstream supply chain.

Maritime crude oil transportation – A split pickup and split delivery problem

The maritime oil tanker routing and scheduling problem is known to the literature since before 1950. In the presented problem, oil tankers transport crude oil from supply points to demand locations around the globe. The objective is to find ship routes, load sizes, as well as port arrival and departure times, in a way that minimizes transportation costs. We introduce a path flow model where paths are ship routes. Continuous variables distribute the cargo between the different routes. Multiple products are transported by a heterogeneous fleet of tankers. Pickup and delivery requirements are not paired to cargos beforehand and arbitrary split of amounts is allowed. Small realistic test instances can be solved with route pre-generation for this model. The results indicate possible simplifications and stimulate further research.

Crude Oil Tanker Routing and Scheduling

Abstract This paper illustrates how operations research can be applied to large-scale maritime crude oil transportation. The more the industry strives to improve the efficiency of their supply chains the more complex and involved planning tasks become. Crude oil tanker routing and scheduling is a good example for a highly complex planning problem in the petroleum and shipping industry. It is also a prevalent problem for which research can provide solutions that exploit the existing potential for improvement. We describe the maritime transportation part of the crude oil supply chain which we denote as the crude oil tanker routing and scheduling problem (COTRASP). Throughout this article, mathematical notation is used as a method to illustrate the various aspects of the problem. Cited literature shows the efforts made to guarantee efficient transportation and realize cost savings in related problems. Finally, solution approaches are discussed and suggestions for further research are made.

Alternative approaches to the crude oil tanker routing and scheduling problem with split pickup and split delivery

The crude oil tanker routing and scheduling problem with split pickup and split delivery is a maritime transportation task where an industrial operator needs to ship different types of crude oil from production sites to oil refineries. The different crude oils are supplied and demanded in many ports in certain time windows. Pickup and delivery quantities are known in advance but no pairing of pickup and delivery needs to be predefined and can be decided together with shipment quantities during optimization. Pickup and delivery quantities may be split arbitrarily among the ships in the fleet. We compare two alternative path flow model approaches to investigate their degree of applicability in a column generation setup. For this purpose we apply route pregeneration prior to optimization. The first approach uses continuous decision variables for pickup and delivery to decide on shipment quantities. In the considerably shorter second formulation cargo quantities are discretized and included into the paths. The second approach is capable to solve larger instances and is more efficient in terms of computational performance, however solution quality may decrease due to the discretization.