Genaro J. Gutierrez

Algorithms for robust single and multiple period layout planning for manufacturing systems

Abstract In many layout design situations, the use of ‘optimality’ with respect to a design objective, such as the minimization of the material handling cost, is insufficiently discriminating. Robustness of the layout, in cases of demand uncertainty, is more important for the manufacturing manager. A robust layout is one that is close to the optimal solution for a wide variety of demand scenarios even though it may not be optimal under any specific demand scenario. In this paper, we develop algorithms to generate robust layout designs for manufacturing systems. Our robustness approach to the layout decision making can be applied to single and multiple period problems in the presence of considerable uncertainty, both in terms of products to be produced as well as their production volumes. Our algorithms, executed in a heuristic fashion, can be effectively used for layout design of large size manufacturing systems.

A robustness approach to uncapacitated network design problems

Abstract In this paper, we address uncapacitated network design problems characterised by uncertainty in the input data. Network design choices have a determinant impact on the effectiveness of the system. Design decisions are frequently made with a great degree of uncertainty about the conditions under which the system will be required to operate. Instead of finding optimal designs for a given future scenario, designers often search for network configurations that are “good” for a variety of likely future scenarios. This approach is referred to as the “robustness” approach to system design. We present a formal definition of “robustness” for the uncapacitated network design problem, and develop algorithms aimed at finding robust network designs. These algorithms are adaptations of the Benders decomposition methodology that are tailored so they can efficiently identify robust network designs. We tested the proposed algorithms on a set of randomly generated problems. Our computational experiments showed two important properties. First, robust solutions are abundant in uncapacitated network design problems, and second, the proposed algorithms performance is satisfactory in terms of cost and number of robust network designs obtained.

A periodic review inventory system with two supply modes

Abstract We describe a periodic review inventory system in which there are two modes of resupply, namely a regular mode and an emergency mode. Orders placed through the emergency channel have a shorter supply lead time but are subject to higher ordering costs compared to orders placed through the regular channel. We analyze this problem within the framework of an order-up-to-R inventory control policy. At each epoch, the inventory manager must decide which of the two supply modes to use and then order enough units to raise the inventory position to a level R. We show that given any non-negative order-up-to level, either only the regular supply mode is used, or there exists an indifference inventory level such that if the inventory position at the review epoch is below the indifference inventory level, the emergency supply mode is used. We also develop procedures for solving for the two policy parameters, i.e., the order-up-to level and the indifference inventory level.

Optimal control policies for a periodic review inventory system with emergency orders

We describe a periodic review inventory system where emergency orders, which have a shorter supply lead time but are subject to higher ordering cost compared to regular orders, can be placed on a continuous basis. We consider the periodic review system in which the order cycles are relatively long so that they are possibly larger than the supply lead times. Study of such systems is important since they are often found in practice. We assume that the difference between the regular and emergency supply lead times is less than the order-cycle length. We develop a dynamic programming model and derive a stopping rule to end the computation and obtain optimal operation parameters. Computational results are included that support the contention that easily implemented policies can be computed with reasonable effort. q 1998 John Wiley & Sons, Inc. Naval Research Logistics 45: 187 - 204, 1998 Several studies in the literature address this problem. These studies divide into two groups: policy-evaluation studies and policy-optimization studies. The former assume a particular policy form and devise methods for evaluating it, while the latter compute the true optimal policy and solve specific instances of the problem under consideration. While the optimization results are stronger, the policy-evaluation studies typically use simpler policies and broader assumptions. This paper contributes to the optimization literature, and the model here is more general than those of early studies.

A robustness approach to international sourcing

An important advantage of the use of international sourcing networks (i.e. selection of suppliers in various countries to support the demands of the firms international factory network) is the resulting hedging power against real exchange rate changes in the international environment. Due to the uncertainty of future real exchange rate changes, the international manager wants to develop a sourcing network that is relatively insensitive (i.e. robust) to the potential changes of the macroeconomic parameters over a planning horizon. In our paper, we formally develop arobust approach to international sourcing. This approach develops the international supplier network in a way that adequately hedges the firms performance against the worst contingency in terms of realizable real exchange rate shocks over a planning horizon. We present an algorithm to obtain theN best robust solutions (i.e. sourcing networks) to the international sourcing problem. Some computational results on the effectiveness of the approach are provided. We also demonstrate how the approach can be used to evaluate various sourcing strategies.

Analysis of the Effects of Uncertainty, Risk-Pooling, and Subcontracting Mechanisms on Project Performance

The problem of designing a contract mechanism to allocate the component subprojects of a large project to a pool of contractors has important implications for project success. Our research analytically addresses issues involved in diversifying risk for the project owner by partitioning the project and assigning the subprojects to multiple contractors whose performance characteristics are imperfectly known. We begin by giving a precise analytical treatment of the effect of activity variance on expected project duration, characterizing the cases when an increase in activity variance pushes up the expected project duration. In the case of a homogeneous project consisting of serial subprojects, we show that disaggregating the project and assigning the subprojects to the contractors on a piecemeal basis reduces variance of project duration while leaving the mean unchanged. On the other hand, in the case of a homogeneous project consisting of parallel subprojects, aggregating the subprojects and assigning the aggregated project to one of the contractors reduces mean project duration.

Heuristic unidirectional flowpath design approaches for automated guided vehicle systems

SUMMARY In this paper, we address the flowpath design issue of automated guided vehicle systems (AGVSs). In particular we concentrate on the design of unidirectional flowpaths (i.e. vehicles are restricted to travel only in one direction along a given segment of the flowpath). We have developed five different heuristics for the design of unidirectional AGVSs. We have also developed simulated annealing algorithms for the above problem. Our extensive computational results indicate that a composite heuristic (i.e. one that combines the most successful of our five heuristics) yields solutions of comparable quality in a fraction of the time required by simulated annealing. For large-size flowpath design problems, we advocate the usage of composite heuristics over simulated annealing, and in particular for the cases in which inaccurate estimates for the input data in our design problem exist

Multiechelon Procurement and Distribution Policies for Traded Commodities

We consider a firm that procures and distributes a commodity from spot and forward markets under randomly fluctuating prices; the commodity is distributed downstream to a set of nonhomogeneous retailers to satisfy random demand. We formulate a model that allows one to compute approximate, but near optimal, procurement and distribution policies for this system, and we explore the value of the commoditys market in providing managers with (a) additional flexibility in procurement and (b) information on price dynamics generated through the trading of futures contracts. Our results indicate that the presence of the commodity market and the information that it conveys may lead to significant reductions in inventory-related costs; however, to obtain these benefits, both the spot procurement flexibility and the term structure of prices generated by the commodity market must be incorporated in the formulation of the operating policy. Managerial insights on the procurement strategy as a function of variability in prices and demand are also discussed. This paper was accepted by John Birge, focused issue editor.

Effect of increasing component commonality on service level and holding cost

We investigate the effect of increasing component commonality in an assemble-to-order system. Numerical investigation of two end products that share up to three components, and whose demands are identically distributed according to either the exponential or the geometric distribution, shows that increasing component commonality results in increasing marginal returns when the criteria are aggregate service level and aggregate stock requirement. For arbitrary end-product demands and general service measures, it is shown that the optimal holding cost for a given service level is concave in the level of commonality.

Mean sample spacings, sample size and variability in an auction-theoretic framework

In terms of a standard model for English auctions and sealed-bid auctions, we study the impact of an increase in bidding competition and in variance of the distribution of valuations on the winners expected rent using tools from order statistics and stochastic ordering.