Many‐player rendezvous search: Stick together or split and meet?

Rendezvous search finds the strategies that players should use in order to find one another when they are separated in a region. Previous papers have concentrated on the case where there are two players searching for one another. This paper looks at the problem when there are more than two players and concentrates on what they should do if some but not all of them meet together. It looks at two strategies—the stick together one and the split up and meet again one. This paper shows that the former is optimal among the class of strategies which require no memory and are stationary, and it gives a method of calculating the expected rendezvous time under it. However, simulation results comparing both strategies suggest that in most situations the split up and meet again strategy which requires some memory leads to faster expected rendezvous times. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48:710–721, 2001     

Optimal service and arrival rates in Jackson queueing networks

In this paper we present an algorithm for solving a class of queueing network design problems. Specifically, we focus on determining both service and arrival rates in an open Jackson network of queueing stations. This class of problems has been widely studied and used in a variety of applications, but not well solved due to the difficulty of the resulting optimization problems. As an example, consider the classic application in computer network design which involves determining the minimum cost line capacities and flow assignments while satisfying a queueing performance measure such as an upper limit on transmission delay. Other application areas requiring the selection of both service and arrival rates in a network of queues include the design of communication, manufacturing, and health care systems. These applications yield optimization problems that are difficult to solve because typically they are nonconvex, which means they may have many locally optimal solutions that are not necessarily globally optimal. Therefore, to obtain a globally optimal solution, we develop an efficient branch and bound algorithm that takes advantage of the problem structure. Computational testing on randomly generated problems and actual problems from a health care organization indicate that the algorithm is able to solve realistic sized problems in reasonable computing time on a laptop computer. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 1–17, 2000     

Scheduling for parallel dedicated machines with a single server

This paper examines scheduling problems in which the setup phase of each operation needs to be attended by a single server, common for all jobs and different from the processing machines. The objective in each situation is to minimize the makespan. For the processing system consisting of two parallel dedicated machines we prove that the problem of finding an optimal schedule is N P‐hard in the strong sense even if all setup times are equal or if all processing times are equal. For the case of m parallel dedicated machines, a simple greedy algorithm is shown to create a schedule with the makespan that is at most twice the optimum value. For the two machine case, an improved heuristic guarantees a tight worst‐case ratio of 3/2. We also describe several polynomially solvable cases of the later problem. The two‐machine flow shop and the open shop problems with a single server are also shown to be N P‐hard in the strong sense. However, we reduce the two‐machine flow shop no‐wait problem with a single server to the Gilmore—Gomory traveling salesman problem and solve it in polynomial time. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 304–328, 2000     

Scheduling to minimize the total compression and late costs

We consider a single-machine scheduling model in which the job processing times are controllable variables with linear costs. The objective is to minimize the sum of the cost incurred in compressing job processing times and the cost associated with the number of late jobs. The problem is shown to be NP-hard even when the due dates of all jobs are identical. We present a dynamic programming solution algorithm and a fully polynomial approximation scheme for the problem. Several efficient heuristics are proposed for solving the problem. Computational experiments demonstrate that the heuristics are capable of producing near-optimal solutions quickly. © 1998 John Wiley & Sons, Inc. Naval Research Logistics 45: 67–82, 1998     

A continuous-review inventory system with lost sales and variable lead time

Using a system-point (SP) method of level crossings, we derive the stationary distribution of the inventory level (stock on hand) in a continuous-review inventory system with compound Poisson demand, Erlang as well as hyperexponentially distributed lead times, and lost sales. This distribution is then used to formulate long-run average cost functions with/without a service level constraint. Some numerical results are also presented, and compared with the Hadley and Whitin heuristic. © 1998 John Wiley & Sons, Inc. Naval Research Logistics 45: 259–278, 1998     

A heuristic approach to bicriteria scheduling

We consider the problem of sequencing jobs on a single machine while minimizing a nondecreasing function of two criteria. We develop a heuristic procedure that quickly finds a good solution for bicriteria scheduling. The procedure is based on using several arcs in the criterion space that are representative of the possible locations of nondominated solutions. By sampling a small number of points on these arcs, a promising point is identified in the criterion space for each arc. An efficient sequence in the neighborhood of each of the promising points is found and the best of these efficient sequences is selected as the heuristic solution. We implement the procedure for two different bicriteria scheduling problems: (i) minimizing total flowtime and maximum tardiness and (ii) minimizing total flowtime and maximum earliness. The computational experience on a wide variety of problem instances show that the heuristic approach is very robust and yields good solutions. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 777–789, 1999     

Cyclical schedules for the joint replenishment problem with dynamic demands

The Joint Replenishment Problem (JRP) involves production planning for a family of items. The items have a coordinated cost structure whereby a major setup cost is incurred whenever any item in the family is produced, and an item-specific minor setup cost is incurred whenever that item is produced. This paper investigates the performance of two types of cyclical production schedules for the JRP with dynamic demands over a finite planning horizon. The cyclical schedules considered are: (1) general cyclical schedules—schedules where the number of periods between successive production runs for any item is constant over the planning horizon—and (2) power-of-two schedules—a subset of cyclical schedules for which the number of periods between successive setups must be a power of 2. The paper evaluates the additional cost incurred by requiring schedules to be cyclical, and identifies problem characteristics that have a significant effect on this additional cost. © 1997 John Wiley & Sons, Inc. Naval Research Logistics 44: 577–589, 1997.     

Computational study of the multiechelon production planning problem

In this article we try to identify appropriate solution procedures for different types of multiechelon production planning problems. We conduct an extensive computational study on uncapacitated multiechelon production planning problems with serial and assembly types of bill-of-material structures. Problems are formulated as both single-source fixed charge network problems and as multicommodity flow problems with fixed charges. Solution procedures considered are branch and cut, Lagrangean relaxation (for the network formulation), and branch and bound (for the multicommodity formulation). Three hundred problems with various problem structures are tested. Our conclusions suggest the best approach for each type of problem structure. © 1997 John Wiley & Sons, Inc.     

Reassessing Military Assistance to the Civil Powers: Are Traditional British Anti-Terrorist Responses Still Effective?

The provision of Military Assistance to the Civil Powers (MACP) encapsulates the traditional approach towards countering terrorism on the British mainland, which emphasises minimum force, proportionality, police primacy and the rule of law, with the military retained as a supporting instrument, being employed only as a measure of last resort. Recent terrorist incidents in major urban centres do, however, question the effectiveness of these established methods. This analysis initially codifies the conceptual issues that underscore the tensions between civil policing and military anti-terrorist approaches in the UK, and proceeds to evaluate and compare a number of operations that indicate the nature of the challenges facing the MACP apparatus. In particular, potential shortcomings in the MACP provisions are identified in the form of threat perception and deployment and enforcement gaps. The assessment finds that there are facets of MACP that are of enduring relevance in the current era, yet a continuing need persists to reconcile police and military imperatives toward serious civil disorder contingencies and conditions of emergency.