Optimization methods for large-scale multiechelon stockage problems

I examine the problem of determining inventory stockage levels and locations of different parts in a multiechelon system. This stockage problem is complicated by parts commonality—each part may be used by several different end items. Stockage levels and locations of each part affect the availability of end items that use the part, since an end item will be out of service if it requires a part that is not available. Of course, if the part is available at another nearby location, then the end item will be out of service for a shorter period of time. An essential feature of any model for this problem is constraints on operational availability of the end items. Because these constraints would involve nonconvex functions if the stockage levels were allowed to vary continuously, I formulate a 0–1 linear optimization model of the stockage problem. In this model, each part can be stocked at any of a number of prespecified levels at each echelon. The model is to minimize stockage cost of the selected items subject to the end-item availability constraints and limits on the total weight, volume, and number of different parts stocked at each echelon. Advantages and disadvantages of different Lagrangian relaxations and the simplex method with generalized upper-bounding capability are discussed for solving this stockage model.     

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     

The Meaning of the Nuclear Evolution: China's Strategic Modernization and US-China Security Relations

Abstract

Will China's development of a new generation of nuclear weapons impact US-China security relations in important ways? One's answer depends on how one views the following: whether or not Chinese leaders believe that they are only now acquiring a secure second strike capability; the scope of coercive power that secure second strike capability provides to conventionally inferior actors; the meaning of China's ‘No First Use’ Doctrine; and the prospects for escalation control in future crises. Applying Cold War theories and tapping Chinese doctrinal writings this article concludes that China's nuclear modernization program might prove more consequential than is commonly believed.