A new robust cycle-based inventory control policy

In this paper, we propose a new robust cycle-based control policy for single installation inventory models with non-stationary uncertain demand. The policy is simple, flexible, easily implementable and preliminary numerical experiments suggest that the policy has very promising empirical performance. The policy can be used both when the excess demand is backlogged as well as … Read more

A Multi-Product Risk-Averse Newsvendor with Exponential Utility Function

We consider a multi-product newsvendor using an exponential utility function. We first establish a few basic properties for the newsvendor regarding the convexity of the model and monotonicity of the impact of risk aversion on the solution. When the product demands are independent and the ratio of the degree of risk aversion to the number … Read more

A Multi-Product Risk-Averse Newsvendor with Law Invariant Coherent Measures of Risk

We consider a multi-product newsvendor under the law-invariant coherent risk measures. We first establish a few fundamental properties of the model regarding the convexity of the problem, the symmetry of the solution and the impact of risk aversion. Specifically, we show that for identical products with independent demands, increased risk aversion leads to decreased orders. … Read more

A Hierarchy of Near-Optimal Policies for Multi-stage Adaptive Optimization

In this paper, we propose a new tractable framework for dealing with multi-stage decision problems affected by uncertainty, applicable to robust optimization and stochastic programming. We introduce a hierarchy of polynomial disturbance-feedback control policies, and show how these can be computed by solving a single semidefinite programming problem. The approach yields a hierarchy parameterized by … Read more

Exact and heuristic solutions of the global supply chain problem with transfer pricing

We examine the example of a multinational corporation that attempts to maximize its global after tax profits by determining the flow of goods, the transfer prices, and the transportation cost allocation between each of its subsidiaries. Vidal and Goetschalckx (2001) proposed a bilinear model of this problem and solved it by an Alternate heuristic. We … Read more

A CONSTRUCTIVE HEURISTIC FOR THE INTEGRATED INVENTORY-DISTRIBUTION PROBLEM

We study the integrated inventory distribution problem which is concerned with multiperiod inventory holding, backlogging, and vehicle routing decisions for a set of customers who receive units of a single item from a depot with infinite supply. We consider an environment in which the demand at each customer is deterministic and relatively small compared to … Read more

Robust Inventory Management Using Tractable Replenishment Policies

We propose tractable replenishment policies for a multi-period, single product inventory control problem under ambiguous demands, that is, only limited information of the demand distributions such as mean, support and deviation measures are available. We obtain the parameters of the tractable replenishment policies by solving a deterministic optimization problem in the form of second order … Read more

Integer Programming Solution Approach for Inventory-Production-Distribution Problems with Direct Shipments

We construct an integrated multi-period inventory-production-distribution replenishment plan for three-stage supply chains. The supply chain maintains close-relationships with a small group of suppliers, and the nature of the products (bulk, chemical, etc.) makes it more economical to rely upon a direct shipment, full-truck load distribution policy between supply chain nodes. In this paper, we formulate … Read more

Step decision rules for multistage stochastic programming: a heuristic approach

Stochastic programming with step decision rules, SPSDR, is an attempt to overcome the curse of computational complexity of multistage stochastic programming problems. SPSDR combines several techniques. The first idea is to work with independent experts. Each expert is confronted with a sample of scenarios drawn at random from the original stochastic process. The second idea … Read more