Search and the introduction of improved technologies

Modeling R&D as standard sequential search, we consider a monopolist who can implement a sequence of technological discoveries during the technology search process: he earns revenue on his installed technology while he engages in R&D to find improved technology. What is not standard is that he has a finite number of opportunities to introduce improved technology. We show that his optimal policy is characterized by thresholds ξ_i(x): introduce the newly found technology if and only if it exceeds ξ_i(x) when x is the state of the currently installed technology and i is the number of remaining introductions allowed. We also analyze a nonstationary learning‐by‐doing model in which the monopolist's experience in implementing new technologies imparts increased capability in generating new technologies. Because this nonstationary model is not in the class of monotone stopping problems, a number of surprising results hold and several seemingly obvious properties of the stationary model no longer hold. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

Implicit enumeration based algorithms for postoptimizing zero-one programs

It has been shown by G. Roodman that useful postoptimization capabilities for the 0-1 integer programming problem can be obtained from an implicit enumeration algorithm modified to classify and collect all fathomed partial solutions. This paper extends the the approach as follows: 1) Improved parameter ranging formulas are obtained by higher resolution classification criteria. 2) Parameters may be changed so as to tighten the original problem, in addition to relaxing it. 3) An efficient storage structure is presented to cope with difficult data collection task implicit in this approach. 4) Finally, computer implementation is facilitated by the elaboration of a unified set of algorithms.     

Class scheduling algorithms for Navy training schools

The problem of developing good schedules for Navy C-Schools has been modeled as a combinatorial optimization problem. The only complicating feature of the problem is that classes must be grouped together into sequences known as pipelines. An ideal schedule will have all classes in a pipeline scheduled in consecutive weeks. The objective is to eliminate the nonproductive time spent by sailors at C-Schools who are waiting for the next class in a pipeline. In this investigation an implicit enumeration procedure for this problem was developed. The key component of our algorithm is a specialized greedy algorithm which is used to obtain a good initial incumbent. Often this initial incumbent is either an optimal schedule or a near optimal schedule. In an empirical analysis with the only other competing software system, our greedy heuristic found equivalent or better solutions in substantially less computer time. This greedy heuristic was extended and modified for the A-School scheduling problem and was found to be superior to its only competitor. © 1998 John Wiley & Sons, Inc. Naval Research Logistics 45: 533–551, 1998     

Attrition modeling in the presence of decoys: An operations-other-than-war motivation

Under various operational conditions, in particular in operations other than war (OOTW) or peacekeeping, an intervening force, here Blue, must occasionally engage in attrition warfare with an opposing force, here Red, that is intermingled with noncombatants. Desirably, Red armed actives are targeted, and not the unarmed noncombatants. This article describes some simple Lanchesterian attrition models that reflect a certain capacity of Blue to discriminate noncombatants from armed and active Red opponents. An explicit extension of the Lanchester square law results: Blue's abstinence concerning the indiscriminate shooting of civilians mixed with Red's is essentially reflected in a lower Blue rate of fire and less advantageous exchange rate. The model applies to other situations involving decoys, and reflects the value of a discrimination capability. © 1997 John Wiley & Sons, Inc. Naval Research Logistics 44 : 507–514, 1997     

Effects of cueing in cooperative search

We consider the effects of cueing in a cooperative search mission that involves several autonomous agents. Two scenarios are discussed: one in which the search is conducted by a number of identical search‐and‐engage vehicles and one where these vehicles are assisted by a search‐only (reconnaissance) asset. The cooperation between the autonomous agents is facilitated via cueing, i.e., the information transmitted to the agents by a searcher that has just detected a target. The effect of cueing on the target detection probability is derived from first principles using a Markov chain analysis. In particular, it is demonstrated that the benefit of cueing on the system's effectiveness is bounded. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

IED casualties mask the real problem: it's us

Casualty figures suggest that the US/Allied Counter Improvised Explosive Device (C-IED) policy and the present allocation of national assets, resources, and intellectual capital have not been very successful. A number of explanations for why this has been the case are discussed and critiqued here.     

End effects in capacity expansion models with finite horizons

Capacity expansion models are typically formulated in the context of some finite horizon. Because the firm lasts longer than the horizon, a bias can enter into the optimal solution from the model horizon chosen. Recently, Grinold [8] has proposed a “dual-equilibrium method” for ameliorating possible distortions. Although the dual-equilibrium method has superior analytical properties to other methods, it is conceptually more complex. In this paper it is shown that there are situations where the “primal-equilibrium” approach of Manne [15] provides equivalent results and that the use of annualized capital costs in the objective function, although somewhat less efficient, results in a similar model.     

Service levels in distribution systems with random customer order size

An approximate method for measuring the service levels of the warehouse-retailer system operating under (s, S) policy is presented. All the retailers are identical and the demand process at each retailer follows a stationary stuttering Poisson process. This type of demand process allows customer orders to be for a random number of units, which gives rise to the undershoot quantity at both the warehouse and retailer levels. Exact analyses of the distribution of the undershoot quantity and the number of orders place by a retailer during the warehouse reordering lead time are derived. By using this distribution together with probability approximation and other heuristic approaches, we model the behavior of the warehouse level. Based on the results of the warehouse level and on an existing framework from previous work, the service level at the retailer level is estimated. Results of the approximate method are then compared with those of simulation. © 1995 John Wiley & Sons, Inc.