Developing production schedules which balance part usage and smooth production loads for just-in-time production systems

A mixed-model multilevel manufacturing facility running under a just-in-time (JIT) production system is controlled by setting the production schedule for the highest level in the facility, which is usually a mixed-model final assembly line. The schedule is set to achieve the goals of the organization, which under JIT are (1) to keep a constant rate of part usage, and (2) to maintain a smooth production load. In this article we extend earlier work in the literature, which focused on the first goal, by developing scheduling procedures which satisfy both goals. Properties of the resulting production schedules are analyzed and illustrative examples are presented.     

Book reviews

America's Secret Power: the CIA in a Democratic Society. By Loch K. Johnson. Oxford University Press, New York (1989), ISBN 0–19–505490–3, $24.95

The Bundeswehr and Western Security. Edited by Stephen F. Szabo. Houndmills, Basingstoke, and Macmillan, London (1990), ISBN 0–333–49880–1, £45.00

Symbolic Defense: the Cultural Significance of the Strategic Defense Initiative. By Edward Tabor Linenthal. University of Illinois Press, Chicago, IL (1989), ISBN 0–252–01619‐X, $19.95

Rethinking European Security. Edited by Furio Cerutti and Rodolfo Ragionieri. Crane Russak, New York (1990), £29.00

Alternative Conventional Defense Postures in the European Theater, Vol. 1: The Military Balance and Domestic Constraints. Edited by Hans Günter Brauch and Robert Kennedy, Crane Russak, New York (1990), £32.00

The Gulf War. Edited by Hanns Maull and Otto Pick. Pinter, London (1989), ISBN 0–86187–763–2, £36.00     

Radar pulse interleaving for multi‐target tracking

In a multifunction radar, the maximum number of targets that can be managed or tracked is an important performance measure. Interleaving algorithms developed to operate radars exploit the dead‐times between the transmitted and the received pulses to allocate new tracking tasks that might involve transmitting or receiving pulses, thus increasing the capacity of the system. The problem of interleaving N targets involves a search among N! possibilities, and suboptimal solutions are usually employed to satisfy the real‐time constraints of the radar system. In this paper, we present new tight 0–1 integer programming models for the radar pulse interleaving problem and develop effective solution methods based on Lagrangian relaxation techniques. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2004.     

The (s,Q) inventory model with Erlang lead time and deterministic demand

We develop a simple, approximately optimal solution to a model with Erlang lead time and deterministic demand. The method is robust to misspecification of the lead time and has good accuracy. We compare our approximate solution to the optimal for the case where we have prior information on the lead‐time distribution, and another where we have no information, except for computer‐generated sample data. It turns out that our solution is as easy as the EOQ's, with an accuracy rate of 99.41% when prior information on the lead‐time distribution is available and 97.54–99.09% when only computer‐generated sample information is available. Apart from supplying the inventory practitioner with an easy heuristic, we gain insights into the efficacy of stochastic lead time models and how these could be used to find the cost and a near‐optimal policy for the general model, where both demand rate and lead time are stochastic. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004