Kevin C. Furman

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Despite of the practicality of the motivation of the inventory routing problem (IRP), there are few successful implementation stories of IRP based decision support systemswhich utilize optimization algorithms. Besides the fact that the IRP is an extremely challengingoptimizationproblem, simplifications andassumptionsmade in the definition of typical IRP in(More)
Liquefied Natural Gas (LNG) is steadily becoming a common mode for commercializing natural gas. Due to the capital intensive nature of LNG projects, the optimal design of LNG supply chains is extremely important from a profitability perspective. Motivated by the need for a model that can assist in the design analysis of LNG supply chains, we address an LNG(More)
The Environmental Protection Agency introduced Reformulated Gasoline (RFG) requirements as a measure to reduce emissions from gasoline-powered vehicles in certain geographic areas. The EPA developed models for predicting emissions as a function of gasoline properties and established statutory baseline emissions from a representative set of gasolines. RFG is(More)
In this work we present an Outer-Approximation algorithm to obtain the global optimum of a nonconvex Mixed Integer Nonlinear Programming (MINLP) model for the scheduling of crude oil movement at the front-end of a petroleum refinery. The model relies on a continuous time representation making use of transfer events. The proposed technique focuses on(More)
Performance variability of modern mixed-integer programming solvers and possible ways of exploiting this phenomenon present an interesting opportunity in the development of algorithms to solve mixed-integer linear programs (MILPs). We propose a framework using multiple branch-and-bound trees to solve MILPs while allowing them to share information in a(More)
In this paper, we introduce a generalized multiperiod scheduling version of the pooling problem to represent time varying blending systems. A general nonconvex MINLP formulation of the problem is presented. The primary difficulties in solving this optimization problem are the presence of bilinear terms, as well as binary decision variables required to(More)
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(More)
We propose a constraint programming approach for the optimization of inventory routing in the liquefied natural gas industry. We present two constraint programming models that rely on a disjunctive scheduling representation of the problem. We also propose an iterative search heuristic to generate good feasible solutions for these models. Computational(More)