Browsing by Subject "Business logistics--Mathematical models"
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Item Integrating commodity markets in the procurement policies for different supply chain structures(2007) Goel, Ankur, 1976-; Gutierrez, Genaro J.This research develops a mathematical model of procurement for commodities which integrates the arbitrage free pricing models for commodities in Finance with the traditional inventory models of Operations Management. In essence, we develop a model that uses market determined information on spot and futures prices to ascertain the optimal procurement strategy. This research is an attempt to understand how firms should adapt their operating policies in presence of fluctuating commodity prices. In this research we seek to understand how the term structure of futures prices at a commodity market can be used in the formulation of procurement and distribution policies of supply chains under centralized decision making. The difference between spot and futures prices play an important role in the determination of the actual cost of holding a commodity; the cost of holding a unit of a tradable commodity is a random variable whose values are determined by the stochastic evolution of prices at the commodity market, and it is exogenously imposed on the firm. The benefits derived from storing a unit of the commodity, on the other hand, are endogenous to each firm and depends on its operational characteristics. Our research objective is to understand how the internal operational decisions of the firm should be modified as a function of the spot and futures prices observed in the market, in order to achieve an optimal balance between cost and benefits of holding an inventory. We model prices with a stochastic process that allows no risk-free arbitrage opportunities, and in this setting, we characterize optimal procurement and distribution policies for various supply chain structures. In addition, we explore the value of using two factor price model over one-factor price model on procurement costs. Our results suggest that there are substantial cost savings in inventory related costs on incorporating spot and futures price information in the procurement model. Furthermore, two-factor model yields higher cost savings than using a single factor model to forecast prices. Distribution of commodities requires the understanding of price dynamics on the commodity markets as well as the issues related to supply chains. This dissertation is an attempt to contribute to the understanding of this area of research.Item Logistics network design with inventory stocking, time-based service and part commonality(2006) Jeet, Vishv; Kutanoglu, ErhanItem Lot-sizing and inventory routing for a production-distribution supply chain(2008-05) Nananukul, Narameth, 1970-; Bard, Jonathan F.The integration of production and distribution decisions presents a challenging problem for manufacturers trying to optimize their supply chain. At the planning level, the immediate goal is to coordinate production, inventory, and delivery to meet customer demand so that the corresponding costs are minimized. Achieving this goal provides the foundations for streamlining the logistics network and for integrating other operational and financial components of the system. In this paper, a model is presented that includes a single production facility, a set of customers with time varying demand, a finite planning horizon, and a fleet of vehicles for making the deliveries. Demand can be satisfied from either inventory held at the customer sites or from daily product distribution. A procedure centering on a reactive tabu search is developed for solving the full problem. After a solution is found, path relinking is applied to improve the results. A novel feature of the methodology is the use of an allocation model in the form of a mixed integer program to find good feasible solutions that serve as starting points for the tabu search. Lower bounds on the optimum are obtained by solving a modified version of the allocation model. Computational testing on a set of 90 benchmark instances with up to 200 customers and 20 time periods demonstrates the effectiveness of the approach. In all cases, improvements ranging from 10 - 20% were realized when compared to those obtained from an existing greedy randomized adaptive search procedure (GRASP). This often came at a three- to five-fold increase in runtime, however. A hybrid scheme that combines the features of reactive tabu search algorithm and branch-and-price algorithm is also developed. The combined approach takes advantage of the efficiency of the tabu search heuristic and the precision of the branch-and-price algorithm. Branching strategy that is suitable for the problem is proposed. Several advance techniques such as column generation heuristic and rounding heuristic are also implemented to improve the efficiency of the algorithm. Computational testing on standard data sets shows that a hybrid algorithm can practically solve instances with up to 50 customers and 8 time periods which is not possible by standard branch-and-price algorithm alone.