We consider the problem of designating hazardous materials routes in and through a major population center. Initially, we restrict our attention to a minimally connected network (a tree) where we can predict accurately the flows on the network. We formulate the tree design problem as an integer programming problem with an objective of minimizing the total transport risk. Such design problems of moderate size can be solved using commercial solvers. We then develop a simple construction heuristic to expand the solution of the tree design problem by adding road segments. Such additions provide carriers with routing choices, which usually increase risks but reduce costs. The heuristic adds paths incrementally, which allows local authorities to trade off risk and cost. We use the road network of the city of Ravenna, Italy, to demonstrate the solution of our integer programming model and our path-addition heuristic. © 2005 Elsevier Ltd. All rights reserved

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In many production systems a certain level of flexibility in the production capacity is either inherent or can be acquired. In that case, system costs may be decreased by managing the capacity and inventory in a joint fashion. In this paper we consider such a maketo-stock production environment with flexible capacity subject to periodic review under non-stationary stochastic demand, where we allow for positive fixed costs both for initiating production and for acquiring external capacity. Our focus is on tactical-level capacity management which refers to the determination of in-house production capacity while the operational-level integrated capacity and inventory management is executed in an optimal manner. We first develop a simple model to represent this relatively complicated problem. Then we elaborate on the characteristics of the general problem and provide the solution to some special cases. Finally, we develop several useful managerial insights as to the optimal capacity level, the effect of operating at a suboptimal capacity level and the value of utilizing flexible capacity.

We characterize optimal policies of a dynamic lot-sizing/vehicle-dispatching problem under dynamic deterministic demands and stochastic lead times. An essential feature of the problem is the structure of the ordering cost, where a fixed cost is incurred every time a batch is initiated (or a vehicle is hired) regardless of the portion of the batch (or vehicle) utilized. Moreover, for every unit of demand not satisfied on time, holding and backorder costs are incurred. Under mild assumptions we show that the demand of a period is satisfied from at most three distinct production (dispatching) epochs. We devise a dynamic programming algorithm to compute the production/dispatching quantities and times.

W e consider an integrated routing and scheduling problem in hazardous materials transportation where accident rates, population exposure, and link durations on the network vary with time of day. We minimize risk (accident probability multiplied by exposure) subject to a constraint on the total duration of the trip. We allow for stopping at the nodes of the network. We consider four versions of this problem with increasingly more realistic constraints on driving and waiting periods, and propose pseudopolynomial dynamic programming algorithms for each version. We use a realistic example network to experiment with our algorithms and provide examples of the solutions they generate. The computational effort required for the algorithms is reasonable, making them good candidates for implementation in a decision-support system. Many of the routes generated by our models do not exhibit the circuitous behavior common in risk-minimizing routes. The en route stops allow us to take full advantage of the time-varying nature of accident probabilities and exposure and result in the generation of routes that are associated with much lower levels of risk than those where no waiting is allowed.

In our environment, a manufacturer procures material from a supplier and the supplier brings it in bulk to a warehouse. This material is then consigned to the plant area, where it is utilized as an input of the production process. This consignment process is outsourced by the manufacturer and a transportation company is selected via a bidding mechanism. Primarily, we consider the problem of designing parameters of a given contract for the transportation activity. We define three subproblems within the contract design problem that interact with each other to a certain extent. These subproblems are the vehicle dispatching problem, inventory control problem, and contract value problem. We define these problems, exploit their interactions, and propose solution methods. Moreover, we present an approach to design such transportation contracts, which is based on solving these subproblems in an order for an adequate number of contract parameter combinations and selecting the one that minimizes expected total costs for the manufacturer.

In this study, we consider the integrated inventory replenishment and transportation operations in a supply chain where the orders placed by the downstream retailer are dispatched by the upstream warehouse via an in‐house fleet of limited size. We first consider the single‐item single‐echelon case where the retailer operates with a quantity based replenishment policy, (r,Q), and the warehouse is an ample supplier. We model the transportation operations as a queueing system and derive the operating characteristics of the system in exact terms. We extend this basic model to a two‐echelon supply chain where the warehouse employs a base‐stock policy. The departure process of the warehouse is characterized in distribution, which is then approximated by an Erlang arrival process by matching the first two moments for the analysis of the transportation queueing system. The operating characteristics and the expected cost rate are derived. An extension of this system to multiple retailers is also discussed. Numerical results are presented to illustrate the performance and the sensitivity of the models and the value of coordinating inventory and transportation operations.

In a manufacturing system with flexible capacity, inventory management can be coupled with capacity management in order to handle fluctuations in demand more effectively. Typical examples include the effective use of temporary workforce and overtime production. In this paper, we discuss an integrated model for inventory and flexible capacity management under non-stationary stochastic demand with the possibility of positive fixed costs, both for initiating production and for using contingent capacity. We analyze the characteristics of the optimal policies for the integrated problem. We also evaluate the value of utilizing flexible capacity under different settings, which enable us to develop managerial insights.