Workforce-constrained maintenance scheduling for military aircraft fleet: a case study

The problem is related to a fleet of military aircraft with a certain flying program in which the availability of the aircraft sufficient to meet the flying program is a challenging issue. During the pre- or after-flight inspections, some component failures of the aircraft may be found. In such cases, the aircraft are sent to the repair shop to be scheduled for maintenance jobs, consisting of failure repairs or preventive maintenance tasks. The objective is to schedule the jobs in such a way that sufficient number of aircrafts is available for the next flight programs. The main resource, as well as the main constraint, in the shop is skilled-workforce. The problem is formulated as a mixed-integer mathematical programming model in which the network flow structure is used to simulate the flow of aircraft between missions, hanger and repair shop. The proposed model is solved using the classical Branch-and-Bound method and its performance is verified and analyzed in terms of a number of test problems adopted from the real data. The results empirically supported practical utility of the proposed model.     

A risk management system for sustainable fleet replacement

This article analyzes the fleet management problem faced by a firm when deciding which vehicles to add to its fleet. Such a decision depends not only on the expected mileage and tasks to be assigned to the vehicle but also on the evolution of fuel and CO₂ emission prices and on fuel efficiency. This article contributes to the literature on fleet replacement and sustainable operations by proposing a general decision support system for the fleet replacement problem using stochastic programming and conditional value at risk (CVaR) to account for uncertainty in the decision process. The article analyzes how the CVaR associated with different types of vehicle is affected by the parameters in the model by reporting on the results of a real-world case study.     

Optimal policy for a general repair replacement model: average reward case

For a general repair replacement model, we study two types ofreplacement policy.Replacement policy T replaces the systemat time T since the installation or last replacement, whilereplacement policy N replaces the system at the time of Nthfailure. Let T^* and N^* be the optimal among all policies T andN respectively. Under the expected average reward criterion,then we show that the optimal policy N^* is at least as goodas the optimal policy T^*. Furthermore, for a monotone processmodel, we determine the optimal policy N^* explicitly throughtwo different approaches.     

Modelling in the absence of data: a case study of fleet maintenance in a developing country

Adequate and relevant objective data for modelling maintenance decision problems are often incomplete or not readily accessible. This is particularly true in developing countries. In this paper the experience gained between 1991–95 in conducting a maintenance study of an inter-city express bus fleet in a developing country is presented. The lack of available maintenance records and operating data rendered the study the most data-starved maintenance modelling exercise the authors have met before or since. The study required the use of subjective methods to both define the problem and to estimate parameters, and the application of recently developed concepts in maintenance modelling along with snapshot analysis and delay time modelling. This imposed a structured approach to problem recognition and problem solution. The study contributed both directly and indirectly to a change in work culture and to a reduction in bus breakdown rate. The company was re-visited 5?years later specifically to seek evidence of lasting impact. Some evidence existed and is reported in the paper.     

Beat patrolling in urban areas A case study

Urban police patrol work has been analysed in the present paper. Working on the crime-rate, as reported by the police department, a plan has been worked out to ensure an effective police patrol in a given locality. This locality is predominantly a “business/marketing area”. Many problems connected with beat patrol like type of beat, route numbers, beat-ranking and others have been discussed. The analysis will help the police station to understand the beat patrol problem. Alternative beat routes have been suggested, together with deployment. Beat ranking may help in assessing the vulnerability of an area and as such proper steps may be taken in advance to prevent the occurrence of the crime. It is expected that patrolling will be more effective and useful after the implementation of this study.     

Optimal adjustment of manpower-requirement forecasts: A case study of Iran

The manpower forecasting models are frequently used in development planning. The usual approach in these models is to correlate the manpower requirement with the level of economic activities and to declare the forecasted figures as the educational targets of the development plan. In this paper we show that because of uncertainties involved in these forecasts, and due to the lack of a cost consideration mechanism in the above models, the implementation of such an educational plan causes an inefficiency in the society's allocation of resources. We then derive an adjustment rule which modifies the manpower-requirement forecasts based on balancing the trade-offs between the cost of educational and the degree of target realization.For demonstration purposes, we apply the above rule to the case of Iran and, through this application, we introduce a methodology for analyzing the sensitivity of results to different types of errors contained in the manpower-requirement forecasts.     

Multi-criteria modelling of irrigation water market at basin level: A Spanish case study

This paper develops a multi-criteria methodology to simulate irrigation water markets at basin level. For this purpose it is assumed that irrigators try to optimise personal multi-attribute utility functions via their productive decision making process (crop mix), subject to a set of constraints based upon the structural features of their farms. In this sense, farmers with homogeneous behaviour regarding water use have been grouped, such groups being established as “types” to be considered in the whole water market simulation model. This model calculates the market equilibrium through a solution that maximises aggregate welfare, which is quantified as the sum of the multi-attribute utilities reached by each of the participating agents. This methodology has been empirically applied for the Duero Basin (Northern Spain), finding that the implementation of this economic institution would increase economic efficiency and agricultural labour demand, particularly during droughts.     

Optimal equipment replacement without paradoxes: A continuous analysis

Combining known continuous- and discrete-time models of equipment replacement, we show that the optimal equipment lifetime is shorter when the embodied technological change is more intense. The paper has been inspired by a paradox in the equipment replacement raised by Cheevaprawatdomrong and Smith in Oper. Res. Lett. 31 (2003).     

Forecasting business profitability by using classification techniques: A comparative analysis based on a Spanish case

A comparative study of the performance of a number of classificatory devices, both parametric (LDA and Logit) and non-parametric (perceptron neural nets and fuzzy-rule-based classifiers) is conducted, and a Monte Carlo simulation-based approach is used in order to measure the average effects of sample size variations on the predictive performance of each classifier. The paper uses as a benchmark the problem of forecasting the level of profitability of Spanish commercial and industrial companies upon the basis of a set of financial ratios. This case illustrates well a distinctive feature of many financial prediction problems, namely that of being characterized by a high dimension feature space as well as a low degree of separability. Response surfaces are estimated in order to summarize the results. A higher performance of model-free classifiers is generally observed, even for fairly moderate sample sizes.     

Emergy-based urban ecosystem health assessment: A case study of Baotou,China

Ecosystem health has been a hot topic of ecosystem management research for years. Considering the urban area as a complex ecosystem consisted of natural, societal and economic entities, urban ecosystem health assessment is necessary to be conducted for the scientific management and proper ecological restoration. Combining with the ecosystem service function of the urban ecosystem, theoretical framework and methodology of the urban ecosystem health assessment based on emergy are proposed and the temporal variation of the health level of the city are also outlined in this paper. Following the principle of ecosystem health assessment, four major factors, including vigor (V), organizational structure (O), resilience (R) and function maintenance (F), are integrated to construct a novel emergy-based urban ecosystem health index (EUEHI). Based on the EUEHI and comparing with those of five other typical Chinese cities, the case study of Baotou city shows that its urban ecosystem health level is steadily arising despite the year 2001 as a turning point. Due to the emphasis on the resource structure adjustment and utilization efficiency, Baotou has obtained a better organizational structure and service function for the total urban ecosystem.     

Optimal versus satisfactory decision making: a case study of sales with a target

We consider a common managerial problem where an agent strives to achieve a prescribed target. We use this problem as a vehicle for comparing and discussing two approaches to decision making: optimising and “satisficing” (where the latter is a neologism due to H. Simon, 1976 Economics Nobel Prize Winner). We compute the optimising and satisfactory strategies for the problem at hand and highlight the differences in their outcomes.     

Optimal adaptive replacement in a renewal process

In this paper we present an exact method for computing the Weibull renewal function and its derivative for application in maintenance optimization. The computational method provides a solid extension to previous work by which an approximation to the renewal function was used in a Bayesian approach to determine optimal replacement times. In the maintenance scenario, under the assumption an item is replaced by a new one upon failure, the underlying process between planned replacement times is a renewal process. The Bayesian approach takes into account failure and survival information at each planned replacement stage to update the optimal time until the next planned replacement. To provide a simple approach to carry out in practice, we limit the decision process to a one‐step optimization problem in the sequential decision problem. We make the Weibull assumption for the lifetime distribution of an item and calculate accurately the renewal function and its derivative. A method for finding zeros of a function is adapted to the maintenance optimization problem, making use of the availability of the derivative of the renewal function. Furthermore, we develop the maximum likelihood estimate version of the Bayesian approach and illustrate it with simulated examples. The maintenance algorithm retains the adaptive concept of the Bayesian methodology but reduces the computational need. Copyright © 2014 John Wiley & Sons, Ltd.     

Asset replacement for an urban railway using a modified two-cycle replacement model

This paper considers the application of capital replacement models at Mass Transit Railway Corporation Limited (MTRCL), Hong Kong. A particular characteristic of the replacement problems considered is that costs relating to existing equipment are generally constant or increasing only slowly. Consequently, replacement is often driven by technical obsolescence, but other criteria are used for informing decisions. The applicability of traditional OR models of replacement is then problematic. We recommend the use of a modified two-cycle replacement model and compare this model to existing capital replacement models. Issues relating to the estimation of delay costs and failure consequences and their influence on the replacement decision are also considered—this is done using a fixed horizon model, which is a special case of the modified two-cycle model. Track points and escalators are used as particular examples. In addition to modelling recommendations, we discuss the management of asset replacement with emphasis on the procedures necessary to ensure that asset replacement requirements are considered appropriately and effectively. The paper treats, in particular, the procedural issues of asset replacement, and the discussion of asset replacement system methodology reflects the current practise at MTRCL, Hong Kong, and developments within that organization through collaboration with academia. The modified two-cycle replacement model is recommended by us for general replacement applications. The asset replacement procedure is presented as an exemplar for business and industry.     

Optimal replacement policy for a multistate repairable system

In this paper, a deteriorating simple repairable system with k + 1 states, including k failure states and one working state, is studied. The system after repair is not ‘as good as new’ and the deterioration of the system is stochastic. Under these assumptions, we study a replacement policy, called policy N, based on the failure number of the system. The objective is to maximize the long-run expected profit per unit time. The explicit expression of the long-run expected profit per unit time is derived and the corresponding optimal solution may be determined analytically or numerically. Furthermore, we prove that the model for the multistate system in this paper forms a general monotone process model which includes the geometric process repair model as a special case. A numerical example is given to illustrate the theoretical results.     

Optimal replacement policies for a multicomponent reliability system

This paper studies a discrete time, infinite horizon, dynamic programming model for the replacement of components in a binary coherent system. Under quite general conditions, we show that it is optimal to follow a critical component policy (CCP), i.e., a policy specified by a critical component set and the rule: Replace a component if and only if it is failed and in the critical component set. We also discuss the problem of computing such policies.     

Optimal transport and a bilevel location-allocation problem

In this paper a two-stage optimization model is studied to find the optimal location of new facilities and the optimal partition of the consumers (location-allocation problem). The social planner minimizes the social costs, i.e. the fixed costs plus the waiting time costs, taking into account that the citizens are partitioned in the region according to minimizing the capacity costs plus the distribution costs in the service regions. By using optimal transport tools, existence results of solutions to the location-allocation problem are presented together with some examples.     

Optimal control of terrorism and global reputation: A case study with novel threshold behavior

A control model is presented which studies optimal spending for the fight against terrorism. Under the assumptions that economic damages are larger the greater the number of terrorists and that the success of counter terror operations depends on public opinion, it is demonstrated that a so-called DNSS threshold may exist, separating the basin of attraction of optimal paths.