Optimal maintenance policies for a safety‐critical system and its deteriorating sensor

We consider the integrated problem of optimally maintaining an imperfect, deteriorating sensor and the safety‐critical system it monitors. The sensor's costless observations of the binary state of the system become less informative over time. A costly full inspection may be conducted to perfectly discern the state of the system, after which the system is replaced if it is in the out‐of‐control state. In addition, a full inspection provides the opportunity to replace the sensor. We formulate the problem of adaptively scheduling full inspections and sensor replacements using a partially observable Markov decision process (POMDP) model. The objective is to minimize the total expected discounted costs associated with system operation, full inspection, system replacement, and sensor replacement. We show that the optimal policy has a threshold structure and demonstrate the value of coordinating system and sensor maintenance via numerical examples. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 399–417, 2017     

Alleviating time inconsistent behaviors via a competition scheme

Under quasi‐hyperbolic discounting, the valuation of a payoff falls relatively rapidly for earlier delay periods, but then falls more slowly for longer delay periods. When the salespersons with quasi‐hyperbolic discounting consider the product sale problem, they would exert less effort than their early plan, thus resulting in losses of future profit. We propose a winner‐takes‐all competition to alleviate the above time inconsistent behaviors of the salespersons, and allow the company to maximize its revenue by choosing an optimal bonus. To evaluate the effects of the competition scheme, we define the group time inconsistency degree of the salespersons, which measures the consequence of time inconsistent behaviors, and two welfare measures, the group welfare of the salespersons and the company revenue. We show that the competition always improves the group welfare and the company revenue as long as the company chooses to run the competition in the first place. However, the effect on group time inconsistency degree is mixed. When the optimal bonus is moderate (extreme high), the competition motivates (over‐motivates) the salesperson to work hard, thus alleviates (worsens) the time inconsistent behaviors. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 357–372, 2017     

Probabilistic resource pooling games

We study a setting with a single type of resource and with several players, each associated with a single resource (of this type). Unavailability of these resources comes unexpectedly and with player‐specific costs. Players can cooperate by reallocating the available resources to the ones that need the resources most and let those who suffer the least absorb all the costs. We address the cost savings allocation problem with concepts of cooperative game theory. In particular, we formulate a probabilistic resource pooling game and study them on various properties. We show that these games are not necessarily convex, do have non‐empty cores, and are totally balanced. The latter two are shown via an interesting relationship with Böhm‐Bawerk horse market games. Next, we present an intuitive class of allocation rules for which the resulting allocations are core members and study an allocation rule within this class of allocation rules with an appealing fairness property. Finally, we show that our results can be applied to a spare parts pooling situation.     

Determining a threshold control policy for an imperfect production system with rework jobs

Consider a threshold control policy for an imperfect production system with only a work center handling both regular and rework jobs. An imperfect production system studied here, generates defect jobs by factors other than machine failures. A threshold control or (ω, s) policy sets the guideline for a work center to switch between regular and rework jobs. A production cycle begins with loading and processing of several batches of regular jobs with a lot size equal to s. The outcome of each completed regular job is an independent Bernoulli trial with three possibilities: good, rework, or scrap. Once the work center accumulates more than a threshold ω of rework jobs, it finishes the last batch of regular jobs and switches to rework jobs. The objective of this research is to find a threshold ω and a lot size s that maximize the average long‐term profit. The ultimate goal is to construct a simple algorithm to search for ω and s that can be implemented directly in production management systems, as a result of this work. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 273–301, 1999     

设备的一种计划维修策略

本文根据设备在全寿命内有事后修理、计划修理和最后报废的实际情况,以全寿命内单位时间的更新维修期望费用最少为目标函数,建立一种数学模型,寻求设备在全寿命内最佳计划修理次数N和最佳的一组计划维修时间间隔集T。     

Determination of burn‐in parameters and residual life for highly reliable products

Today, many products are designed and manufactured to function for a long period of time before they fail. Determining product reliability is a great challenge to manufacturers of highly reliable products with only a relatively short period of time available for internal life testing. In particular, it may be difficult to determine optimal burn‐in parameters and characterize the residual life distribution. A promising alternative is to use data on a quality characteristic (QC) whose degradation over time can be related to product failure. Typically, product failure corresponds to the first passage time of the degradation path beyond a critical value. If degradation paths can be modeled properly, one can predict failure time and determine the life distribution without actually observing failures. In this paper, we first use a Wiener process to describe the continuous degradation path of the quality characteristic of the product. A Wiener process allows nonconstant variance and nonzero correlation among data collected at different time points. We propose a decision rule for classifying a unit as normal or weak, and give an economic model for determining the optimal termination time and other parameters of a burn‐in test. Next, we propose a method for assessing the product's lifetime distribution of the passed units. The proposed methodologies are all based only on the product's initial observed degradation data. Finally, an example of an electronic product, namely contact image scanner (CIS), is used to illustrate the proposed procedure. © 2002 Wiley Periodicals, Inc. Naval Research Logistics, 2003     

What Is Known About Defence Research And Development Spill-Overs?

This article surveys the body of available evidence regarding the spill-over effects of defence R&D. It reviews the routes through which defence R&D spills over to the economy with positive externalities – in terms of new products, technologies or processes; the barriers that impede or block such a process; potential negative repercussions, and the measure of such effects. The main conclusion is that the uncertainty of these effects, and the inaccurate appraisal of their value, hardly supports informed decisions concerning defence R&D policies.     

An attacker‐defender model for analyzing the vulnerability of initial attack in wildfire suppression

Wildfire managers use initial attack (IA) to control wildfires before they grow large and become difficult to suppress. Although the majority of wildfire incidents are contained by IA, the small percentage of fires that escape IA causes most of the damage. Therefore, planning a successful IA is very important. In this article, we study the vulnerability of IA in wildfire suppression using an attacker‐defender Stackelberg model. The attacker's objective is to coordinate the simultaneous ignition of fires at various points in a landscape to maximize the number of fires that cannot be contained by IA. The defender's objective is to optimally dispatch suppression resources from multiple fire stations located across the landscape to minimize the number of wildfires not contained by IA. We use a decomposition algorithm to solve the model and apply the model on a test case landscape. We also investigate the impact of delay in the response, the fire growth rate, the amount of suppression resources, and the locations of fire stations on the success of IA.     

Adjacency‐based local top‐down search method for finding maximal efficient faces in multiple objective linear programming

It is well‐known that the efficient set of a multiobjective linear programming (MOLP) problem can be represented as a union of the maximal efficient faces of the feasible region. In this paper, we propose a method for finding all maximal efficient faces for an MOLP. The new method is based on a condition that all efficient vertices (short for the efficient extreme points and rays) for the MOLP have been found and it relies on the adjacency, affine independence and convexity results of efficient sets. The method uses a local top‐down search strategy to determine maximal efficient faces incident to every efficient vertex for finding maximal efficient faces of an MOLP problem. To our knowledge, the proposed method is the first top‐down search method that uses the adjacency property of the efficient set to find all maximal efficient faces. We discuss this and other advantages and disadvantages of the algorithm. We also discuss some computational experience we have had with our computer code for implementing the algorithm. This computational experience involved solving several MOLP problems with the code.     

On efficient algorithms for finding efficient salvo policies

We consider the salvo policy problem, in which there are k moments, called salvos, at which we can fire multiple missiles simultaneously at an incoming object. Each salvo is characterized by a probability p_i: the hit probability of a single missile. After each salvo, we can assess whether the incoming object is still active. If it is, we fire the missiles assigned to the next salvo. In the salvo policy problem, the goal is to assign at most n missiles to salvos in order to minimize the expected number of missiles used. We consider three problem versions. In Gould's version, we have to assign all n missiles to salvos. In the Big Bomb version, a cost of B is incurred when all salvo's are unsuccessful. Finally, we consider the Quota version in which the kill probability should exceed some quota Q. We discuss the computational complexity and the approximability of these problem versions. In particular, we show that Gould's version and the Big Bomb version admit pseudopolynomial time exact algorithms and fully polynomial time approximation schemes. We also present an iterative approximation algorithm for the Quota version, and show that a related problem is NP-complete.