A PAVEMENT MANAGEMENT DECISION SUPPORT SYSTEM

We present a pavement management expert system developed by the University of Wisconsin-Madison and implemented within a geographical information system for the Wisconsin Department of Transportation. The system uses pavement data regularly collected on the state's 12,000 miles of highway to assist engineers, planners, and budget analysts' management decisions about pavements to be included in 6-year improvement and 3-year maintenance programs. The system has a three-layer architecture. The lowest level suggests treatments for each of a large number of small segments of highway. The middle layer aggregates segments, suggests alternative treatments, and estimates the cost of each. The top layer prioritizes the projects and incorporates them into intermediate-range plans. The geographical information system environment enables integration of existing databases within the system using a topologically structured geographic database and specialized software.     

Implementation of Equity in Resource Allocation for Regional Earthquake Risk Mitigation Using Two‐Stage Stochastic Programming

This article presents a new methodology to implement the concept of equity in regional earthquake risk mitigation programs using an optimization framework. It presents a framework that could be used by decisionmakers (government and authorities) to structure budget allocation strategy toward different seismic risk mitigation measures, i.e., structural retrofitting for different building structural types in different locations and planning horizons. A two‐stage stochastic model is developed here to seek optimal mitigation measures based on minimizing mitigation expenditures, reconstruction expenditures, and especially large losses in highly seismically active countries. To consider fairness in the distribution of financial resources among different groups of people, the equity concept is incorporated using constraints in model formulation. These constraints limit inequity to the user‐defined level to achieve the equity‐efficiency tradeoff in the decision‐making process. To present practical application of the proposed model, it is applied to a pilot area in Tehran, the capital city of Iran. Building stocks, structural vulnerability functions, and regional seismic hazard characteristics are incorporated to compile a probabilistic seismic risk model for the pilot area. Results illustrate the variation of mitigation expenditures by location and structural type for buildings. These expenditures are sensitive to the amount of available budget and equity consideration for the constant risk aversion. Most significantly, equity is more easily achieved if the budget is unlimited. Conversely, increasing equity where the budget is limited decreases the efficiency. The risk‐return tradeoff, equity‐reconstruction expenditures tradeoff, and variation of per‐capita expected earthquake loss in different income classes are also presented.     

Cooperative Advertising and Pricing in a Dynamic Stochastic Supply Chain: Feedback Stackelberg Strategies

Cooperative (co‐op) advertising is an important instrument for aligning manufacturer and retailer decisions in supply chains. In this, the manufacturer announces a co‐op advertising policy, i.e., a participation rate that specifies the percentage of the retailer's advertising expenditure that it will provide. In addition, it also announces the wholesale price. In response, the retailer chooses its optimal advertising and pricing policies. We model this supply chain problem as a stochastic Stackelberg differential game whose dynamics follows Sethi's stochastic sales‐advertising model. We obtain the condition when offering co‐op advertising is optimal for the manufacturer. We provide in feedback form the optimal advertising and pricing policies for the manufacturer and the retailer. We contrast the results with the advertising and price decisions of the vertically integrated channel, and suggest a method for coordinating the channel.     

Uncovering the Distribution of Motorists' Preferences for Travel Time and Reliability

We apply recent econometric advances to study the distribution of commuters' preferences for speedy and reliable highway travel. Our analysis applies mixed logit to combined revealed and stated preference data on commuter choices of whether to pay a toll for congestion‐free express travel. We find that motorists exhibit high values of travel time and reliability, and substantial heterogeneity in those values. We suggest that road pricing policies designed to cater to such varying preferences can improve efficiency and reduce the disparity of welfare impacts compared with recent pricing experiments.     

Reassessing Tradeoffs Inherent to Simultaneous Maintenance and Production Planning

Previous work has considered the simultaneous (as opposed to sequential) optimization of a maintenance policy and a production policy in a multi‐product setting with random yield and product mix constraints. One of the sequential approaches to which the simultaneous approach is compared is a so‐called first‐come‐first‐served (FCFS) approach, i.e., an approach that generates randomized production policies that do not depend on the deterioration state of the machine. However, the model formulation for this approach does not generate policies consistent with this FCFS notion. Therefore, we present a revised FCFS model and analyze its performance using an existing experimental design. The results suggest that previous work overestimates the degree to which a FCFS approach is suboptimal, and underestimates the value of simultaneously optimizing the maintenance and production decisions. Lastly, we conduct additional experiments which suggest that the joint impact of using both simultaneous optimization and a deterioration dependent production policy is quite significant.     

PUBLIC EDUCATION AND PENSIONS IN DEMOCRACY: A POLITICAL ECONOMY THEORY

A dynamic political economy theory of fiscal policy is presented to explain the simultaneous existence of public education and pensions in modern democracies. The driving force of the model is the intergenerational conflict over the allocation of the public budget. Successive generations of voters choose fiscal policies through repeated elections. The political power of elderly voters creates the motive for adults to support public investment in the human capital of future generations since it expands future pension possibilities. We characterize the Markov perfect equilibrium of the voting game in a small open economy. The equilibrium reproduces salient features of intergenerational fiscal policies in modern economies.     

Effects of maintenance policies on the productivity of flexible manufacturing cells

Flexible manufacturing cells (FMCs) often operate with increasing failure rate due to extensive utilization and wear-outs of equipment. While maintenance plans can eliminate wear-out failures, random failures are still unavoidable. This paper discusses a procedure that combines simulation and analytical models to analyze the effects of corrective, preventive, and opportunistic maintenance policies on productivity of a flexible manufacturing cell. The production output rate of an FMC, which is a function of availability, is determined under different maintenance policies and mean time between failures.     

On the role of Prognostics and Health Management in advanced maintenance systems

The advanced use of the Information and Communication Technologies is evolving the way that systems are managed and maintained. A great number of techniques and methods have emerged in the light of these advances allowing to have an accurate and knowledge about the systems’ condition evolution and remaining useful life. The advances are recognised as outcomes of an innovative discipline, nowadays discussed under the term of Prognostics and Health Management (PHM). In order to analyse how maintenance will change using PHM, a conceptual model is proposed built upon three views. The model highlights: (i) how PHM may impact the definition of maintenance policies; (ii) how PHM fits within the condition-based maintenance; and (iii) how PHM can be integrated into reliability-centred maintenance programmes. The conceptual model is the research finding of this review note and helps to discuss the role of PHM in advanced maintenance systems.     

Managing “forced” technology transfer in emerging markets: The case of China

This paper explores how foreign multinational corporations (MNCs) manage risks associated with “forced” technology transfer (“FTT”) policies in emerging markets. Although MNCs are increasingly exposed to appropriability risks from these policies, how they respond is relatively understudied in international business (IB) research. We explore this topic based upon a survey and interviews with Western MNCs doing business in China, as well as a discussion about the recent US-China trade war. We find that, as traditional IB theory would predict, internally-oriented strategies (e.g., internalization, maintenance of informal intellectual property (IP), and control of technological centrality and sophistication) are often used to respond to FTT policies; however, the risks from such policies can sometimes be more efficiently managed by externally-oriented strategies (e.g., non-market activities and reliance on formal IP). We discuss how the co-evolution of MNCs' risk management strategies alongside changing value chains, IP institutions, and conditions determining the leverage of FTT policies appear to contribute to this phenomenon. We argue that IB research should more prominently recognize the role of externally-oriented strategies, not only internally-oriented ones, in managing the complex IP-related institutional challenges present in emerging markets today.     

A Comparison of Reorder Point and Material Requirements Planning Inventory Control Logic*

This paper reports the results of simulation experiments that compared the inventory efficiency (i.e., the customer service level provided by a given level of inventory) for two different inventory policies. One of these policies uses time-phased information on future demands like that found in material requirements planning (MRP) systems, while the other (the reorder point or ROP policy) relies on forecasts implicitly based on average past demands. After establishing that the MRP policies dominate for reasonable conditions, the uncertainty of the forecasts was manipulated until the policy preference was reversed. It requires a very perverse relationship between the forecast and actual demand before ROP beats MRP on inventory efficiency.     

Joint modified block replacement and production/inventory control policy for a failure-prone manufacturing cell

This paper considers a joint preventive maintenance (PM) and production/inventory control policy of an unreliable single machine, mono-product manufacturing cell with stochastic non-negligible corrective and preventive delays. The production/inventory control policy, which is based on the hedging point policy (HPP), consists in building and maintaining a safety stock of finished products in order to respond to demand and to avoid shortages during maintenance actions. Without considering the impact of preventive and corrective actions on the overall performance of the production system, most authors working in the reliability and maintainability domains confirm that the age-based preventive maintenance policy (ARP) outperforms the classical block-replacement policy (BRP). In order to reduce wastage incurred by the classical BRP, we consider a modified block replacement policy (MBRP), which consists in canceling a preventive maintenance action if the time elapsed since the last maintenance action exceeds a specified time threshold. The main objective of this paper is to determine the joint optimal policy that minimizes the overall cost, which is composed of corrective and preventive maintenance costs as well as inventory holding and backlog costs. A simulation model mimicking the dynamic and stochastic behavior of the manufacturing cell, based on more realistic considerations of the real behavior of industrial manufacturing cells, is proposed. Based on simulation results, the joint optimal MBRP/HPP parameters are obtained through a numerical approach that combines design of experiment, analysis of variance and response surface methodologies. The joint optimal MBRP/HPP policy is compared to classical joint ARP/HPP and BRP/HPP optimal policies, and the results show that the proposed MBRP/HPP outperforms the latter. Sensitivity analyses are also carried out in order to confirm the superiority of the proposed MBRP/HPP, and it is observed that for practitioners, the proposed joint MBRP/HPP offers not only cost savings, but is also easy to manage, as compared to the ARP/HPP policy.     

纵向沟通中隐性信息获取的激励兼容机制研究

下属隐性信息的获取是确保上级决策者有效决策的一个重要基础,现有的研究未能解决隐性信息获取的效率问题与预算平衡的两难问题。本文通过确认决策者的作用,在分析模型中引入决策者成本,并借鉴政府征收"所得税"的思路,不仅解决了隐性信息获取的真实性,而且解决了原有方案未能同时兼顾的预算平衡、利润最大化以及向下属转移损失等问题。     

A hybrid BA-VNS algorithm for coordinated serial-batching scheduling with deteriorating jobs,financial budget,and resource constraint in multiple manufacturers

We study a coordinated serial-batching scheduling problem that features deteriorating jobs, financial budget, resource constraints, resource-dependent processing times, setup times, and multiple manufacturers simultaneously. A unique feature but also a significant challenge in this problem is the dual constraints on resources, i.e., financial budget and resource quantity. Some key structural properties are first identified for the setting where the jobs and resources are already assigned to each manufacturer, which enables us to develop the optimal resource allocation scheme. Then, a polynomial-time scheduling rule is proposed to search for the optimal solution for each manufacturer in this setting. Then, a hybrid BA-VNS algorithm combining Bat algorithm (BA) and variable neighborhood search (VNS) is proposed to tackle the studied problem, and the optimal scheduling rule is implemented in its encoding procedure. Finally, computational experiments are conducted to test the performance of the proposed algorithm, and the efficiency and improvements are compared with those of BA, VNS, and Particle Swarm Optimization (PSO), with respect to convergence speed as well as computational stability.     

Approximate dynamic programming for the aeromedical evacuation dispatching problem: Value function approximation utilizing multiple level aggregation

Sequential resource allocation decision-making for the military medical evacuation of wartime casualties consists of identifying which available aeromedical evacuation (MEDEVAC) assets to dispatch in response to each casualty event. These sequential decisions are complicated due to uncertainty in casualty demand (i.e., severity, number, and location) and service times. In this research, we present a Markov decision process model solved using a hierarchical aggregation value function approximation scheme within an approximate policy iteration algorithmic framework. The model seeks to optimize this sequential resource allocation decision under uncertainty of how to best dispatch MEDEVAC assets to calls for service. The policies determined via our approximate dynamic programming (ADP) approach are compared to optimal military MEDEVAC dispatching policies for two small-scale problem instances and are compared to a closest-available MEDEVAC dispatching policy that is typically implemented in practice for a large-scale problem instance. Results indicate that our proposed approximation scheme provides high-quality, scalable dispatching policies that are more easily employed by military medical planners in the field. The identified ADP policies attain 99.8% and 99.5% optimal for the 6- and 12-zone problem instances investigated, as well as 9.6%, 9.2%, and 12.4% improvement over the closest-MEDEVAC policy for the 6-, 12-, and 34-zone problem instances investigated.     

An Integrated Approach for Assessing the Impact of Large-Scale Future Floods on a Highway Transport System

The negative impact of climate change continues to escalate flood risk. Floods directly and indirectly damage highway systems and disturb the socioeconomic order. In this study, we propose an integrated approach to quantitatively assess how floods impact the functioning of a highway system. The approach has three parts: (1) a multi-agent simulation model to represent traffic, heterogeneous user demand, and route choice in a highway network; (2) a flood simulator using future runoff scenarios generated from five global climate models, three representative concentration pathways (RCPs), and the CaMa-Flood model; and (3) an impact analyzer, which superimposes the simulated floods on the highway traffic simulation system, and quantifies the flood impact on a highway system based on car following model. This approach is illustrated with a case study of the Chinese highway network. The results show that (i) for different global climate models, the associated flood damage to a highway system is not linearly correlated with the forcing levels of RCPs, or with future years; (ii) floods in different years have variable impacts on regional connectivity; and (iii) extreme flood impacts can cause huge damages in highway networks; that is, in 2030, the estimated 84.5% of routes between provinces cannot be completed when the highway system is disturbed by a future major flood. These results have critical implications for transport sector policies and can be used to guide highway design and infrastructure protection. The approach can be extended to analyze other networks with spatial vulnerability, and it is an effective quantitative tool for reducing systemic disaster risk.     

纵向沟通中隐性信息获取的激励兼容机制研究

下属隐性信息的获取是确保上级决策者有效决策的一个重要基础,现有的研究未能解决隐性信息获取的效率与预算平衡的两难问题。本文通过确认决策者的作用,在分析模型中引入决策者成本,并借鉴政府征收“所得税”的思路,不仅解决了隐性信息获取的真实性,而且解决了原有方案未能同时兼顾的预算平衡、利润最大化以及向下属转移损失等问题。     

软预算约束、银行危机与金融监管

本文利用不完全信息动态博弈模型,探讨了金融危机、监管者的软预算约束与银行道德风险之间的关系.研究发现:金融危机愈高,监管者的软预算约束愈大,因此,消除软预算约束是降低金融危机最重要的监管措施;建设性模糊策略能够有效消除金融机构对软预算约束的预期心理;随着银行的道德风险上升,金融危机也会升高.     

Comparison of Subsidy Schemes for Reducing Waiting Times in Healthcare Systems

This study analyzes subsidy schemes that are widely used in reducing waiting times for public healthcare service. We assume that public healthcare service has no user fee but an observable delay, while private healthcare service has a fee but no delay. Patients in the public system are given a subsidy s to use private service if their waiting times exceed a pre‐determined threshold t. We call these subsidy schemes (s, t) policies. As two extreme cases, the (s, t) policy is called an unconditional subsidy scheme if t = 0, and a full subsidy scheme if s is equal to the private service fee. There is a fixed budget constraint so that a scheme with larger s has a larger t. We assess policies using two criteria: total patient cost and serviceability (i.e., the probability of meeting a waiting time target for public service). We prove analytically that, if patients are equally sensitive to delay, a scheme with a smaller subsidy outperforms one with a larger subsidy on both criteria. Thus, the unconditional scheme dominates all other policies. Using empirically derived parameter values from the Hong Kong Cataract Surgery Program, we then compare policies numerically when patients differ in delay sensitivity. Total patient cost is now unimodal in subsidy amount: the unconditional scheme still yields the lowest total patient cost, but the full subsidy scheme can outperform some intermediate policies. Serviceability is unimodal too, and the full subsidy scheme can outperform the unconditional scheme in serviceability when the waiting time target is long.     

Approximation Algorithms for Certain Network Improvement Problems

We study budget constrained network upgrading problems. Such problems aim at finding optimal strategies for improving a network under some cost measure subject to certain budget constraints. Given an edge weighted graph G = (V, E), in the edge based upgrading model, it is assumed that each edge e of the given network also has an associated function ce (t) that specifies the cost of upgrading the edge by an amount t. A reduction strategy specifies for each edge e the amount by which the length (e) is to be reduced. In the node based upgrading model, a node v can be upgraded at an expense of c(v). Such an upgrade reduces the delay of each edge incident on v. For a given budget B, the goal is to find an improvement strategy such that the total cost of reduction is at most the given budget B and the cost of a subgraph (e.g. minimum spanning tree) under the modified edge lengths is the best over all possible strategies which obey the budget constraint.After providing a brief overview of the models and definitions of the various problems considered, we present several new results on the complexity and approximability of network improvement problems.