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.     

A hybrid inventory management system responding to regular demand and surge demand

This paper proposes a hybrid policy for a stochastic inventory system facing regular demand and surge demand. The combination of two different demand patterns can be observed in many areas, such as healthcare inventory and humanitarian supply chain management. The surge demand has a lower arrival rate but higher demand volume per arrival. The solution approach proposed in this paper incorporates the level crossing method and mixed integer programming technique to optimize the hybrid inventory policy with both regular orders and emergency orders. The level crossing method is applied to obtain the equilibrium distributions of inventory levels under a given policy. The model is further transformed into a mixed integer program to identify an optimal hybrid policy. A sensitivity analysis is conducted to investigate the impact of parameters on the optimal inventory policy and minimum cost. Numerical results clearly show the benefit of using the proposed hybrid inventory model. The model and solution approach could help healthcare providers or humanitarian logistics providers in managing their emergency supplies in responding to surge demands.     

Decision analysis and strategic policy formulation

The role of decision analysis in the context of business policy is explored with the aid of a case study of a reorganization situation. This case study provides insights about the implementation of decision analysis in the policy field and also indicates guidelines for managers to follow in adapting the decision analysis approach to the resolution of the policy formulation problem.     

Strategic planning for water—A case history

Choosing a management policy in a developing economy for public utility systems involves consideration of a host of factors and delineation of some strategic issues. In order to make the management policy operational, a formal approach to system planning is necessary. This paper develops an approach whose primary aim is to assess the current status of the system and the environment, to identify and categorize the management problems, and then to break up the problems into manageable components to find out appropriate solution strategies. It is hoped that such an approach will jointly clarify the perceptions of how management techniques can be gainfully used and practised in managing large scale public utility systems.     

EOQ-based inventory management in single-machine multi-item systems

The present paper proposes an approach for including the finite capacity constraint in the EOQ model (and, in more general terms, in inventory systems) to study the context of single-machine multi-item systems. In particular, the proposed approach regulates the processing of different items by a shared resource according to a control model based on an ordering policy that combines the Economic Order Quantity with a policy based on minimum and maximum inventory levels (min–max policy). To achieve such a challenging result, the present work exploits the analogy between “switched arrival systems” (a particular class of hybrid systems) and min-max inventory systems. The development and parameterization of the abovementioned control model, therefore, refers to switched arrival systems control theory and mixed-integer linear programming. The present work also contributes to the integration of static tools (i.e., the EOQ model) and control tools, approaching these areas. The paper concludes with a real case application that illustrates the proposed approach and allows for a future research path to be drawn.     

Joint production and subcontracting planning of unreliable multi-facility multi-product production systems

This article addresses the problem of joint optimization of production and subcontracting of unreliable production systems. The production system considered presents a common problem in the pharmaceutical industry. It is composed of multiple production facilities with different capacities, each of which is capable of producing two different classes of medications (brand name and generic). The resort to subcontracting is double: first, it involves the quantity of products received on a regular basis in order to compensate for insufficient production capacity in existing facilities, second, when needed, urgent orders are also launched in order to reduce the risk of shortages caused by breakdowns of manufacturing facilities. Failures, repairs and urgent delivery times may be represented by any probability distributions.The objective is to propose a general control policy for the system under consideration, and to obtain, in the case of two facilities, optimal control parameters that minimize the total incurred cost for a specific level of the customer service provided. Given the complexity of the problem considered, an experimental optimization approach is chosen in order to determine the optimal control parameters. This approach includes experimental design, analysis of variance, response surface methodology and simulation modeling. It allows the accurate representation of the dynamic and stochastic behaviors of the production system and the assessment of optimal control parameters. Other control parameters which represent the subcontracting are introduced and three joint production/subcontracting control policies (general, urgent, regular) are compared to one another. The proposed joint production/regular subcontracting control policy involves a cost decrease of up to 20%, as compared to results obtained by Dror et al. [1], who used a simplified control policy in addition to a heuristic solution approach for a real case study. This policy offers not only cost savings, but is also easier to manage, as compared to that proposed by Dror et al. [1]. Numerical examples and a sensitivity analysis are also performed to illustrate the robustness of the proposed control policy and the solution approach.     

Coordinating operational policy with financial hedging for risk-averse firms

A risk-averse firm׳s financial hedging activity can impact the decision making in its daily operations. We introduce a CE-based approach that can help the firm to simplify the procedure in making hedging-consistent decisions. A key feature of this new approach is that it allows for the existence of nonfinancial random factors, which give rise to the risk exposure that cannot be hedged in the financial market. By using a CE operator, we show that the optimal operational policy can be obtained by maximizing the CE-based value function. Although the CE operator may bring additional nonlinearity to the value function, we find that the commonly desired base-stock policy can remain optimal under specific conditions. We hope that this new approach can help pave the way for future investigation on joint operations management and financial hedging problems in dynamic settings.     

跨国企业和东道国政府合作共赢的演化博弈和决策研究

基于行为人有限理性具有动机公平偏好的假设,论文定义跨国企业和东道国政府为委托代理关系,构建了企业和政府在不同引资政策下的博弈模型,探讨了跨国企业和东道国政府的演化博弈过程及其均衡点,分析了博弈双方最佳决策以及合作共赢机制。研究表明:东道国政府给予跨国企业的收入分配比越高,跨国企业越努力工作,其最优努力程度还与规制系数、风险规避程度、规模和优惠产出系数相关;东道国政府给予的收入分配比受风险规避度、产出方差和规避系数的影响;在激励与规制相结合的引资政策下,基于动机公平的博弈双方能达到演化稳定点,实现跨国企业和东道国政府合作共赢。本文将演化博弈和合作共赢纳入分析框架中进行动态分析,丰富了该领域的研究成果,为企业对外投资提供了理论依据以及政府政策制定提供了参考。     

A method for exploring the future

This paper describes a method for exploring future policy options. The procedures for choosing the range of options and constructing the future scenarios are described with special emphasis on policy implications. The advantages and limitations of this approach are discussed. The construction of scenarios is illustrated by describing three energy policy options for the U.K. The detailed analysis of these energy options, including their political and resource implications, will be described in a later paper.     

Revenue Management in Order‐Driven Production Systems

This article investigates the effectiveness of a tactical demand‐capacity management policy to guide operational decisions in order‐driven production systems. The policy is implemented via a heuristic that attempts to maximize revenue by selectively accepting or rejecting customer orders for multiple product classes when demand exceeds capacity constantly over the short term. The performance of the heuristic is evaluated in terms of its ability to generate a higher profit compared to a first‐come‐first‐served (FCFS) policy. The policies are compared over a wide range of conditions characterized by variations in both internal (firm) and external (market) factors. The heuristic, when used with a Whole Lot order‐processing approach, produces higher profit compared to FCFS when profit margins of products are substantially different from each other and demand exceeds capacity by a large amount. In other cases it is better to use the heuristic in conjunction with the Split Lot order‐processing approach.     

Nanotechnology,Risk, and Oversight: Learning Lessons from Related Emerging Technologies

Emerging technologies are defined by their novelty and thus are accompanied by significant uncertainty in determining appropriate ways to manage risks associated with them. Yet, there is a body of prior knowledge about risk management and oversight policy for other technologies that have already permeated society. Here, we describe two ways in which prospective oversight policy analysis for emerging technologies can draw upon these past experiences. One involves comparing specific products that have already been marketed to similar products of the emerging technology (cognate‐product approach). The other treats the emerging technology as a body of products and methods and relates it to another technological field that has already emerged and penetrated markets (whole‐technology approach). In this article, we describe our work using these approaches to inform risk and oversight policy for nanotechnology and its products. We draw parallels between biotechnology and nanotechnology as whole fields of development and also between genetically engineered organisms in the food supply and agricultural products of nanotechnology. Through these comparisons, we find that both approaches to historical learning have value and present lessons that could be applied to nanotechnology.     

Implementation of JIT purchasing: An integrated approach

This article addresses the necessity of integration between buyer and supplier for effective implementation of the JIT system. An integrated lot-splitting model of facilitating multiple shipments in small lots is developed and compared with the existing approach in a simple JIT environment, single-buyer-single-supplier, under deterministic conditions for a single product. It is shown that the optimal policy adopted by the integrated approach can provide a strong and consistent cost-minimizing effect for both buyer and supplier over the existing approach.     

供应链库存协调策略研究

研究和分析了直运型供应链通过共同补给期协调库存的策略问题。在该供应链中,单一供应商提供单一产品给面临随机需求的单一零售商。在所提出的库存协调策略条件下,供应商指定共同补给期,当零售商按供应商指定的共同补给期作为其订货周期时,供应商提供零售商一定的价格折扣。这种协调策略可以视为Stackelberg博弈。在阐述了解决该博弈问题的方法后,进行了数值实验,分析了采用这种协调策略的利益。     

The Role of Contract Expirations in Service Parts Management

The majority of after‐sales service providers manage their service parts inventory by focusing on the availability of service parts. This approach, combined with automatic replenishment systems, leads to reactive inventory control policies where base stock levels are adjusted only after a service contract expires. Consequently, service providers often face excess stock of critical service parts that are difficult to dispose due to their specificity. In this study, we address this problem by developing inventory control policies taking into account contract expirations. Our key idea is to reduce the base stock level of the one‐for‐one policy before obsolescence (a full or partial drop in demand rate) occurs and let demand take away excess stock. We refer to this policy as the single‐adjustment policy. We benchmark the single‐adjustment policy with the multiple‐adjustment policy (allowing multiple base stock adjustments) formulated as a dynamic program and verify that for a wide range of instances the single‐adjustment policy is an effective heuristic for the multiple‐adjustment policy. We also compare the single‐adjustment policy with the world‐dependent base stock policy offered by Song and Zipkin (1993) and identify the parameter combinations where both policies yield similar costs. We consider two special cases of the single‐adjustment policy where the base stock level is kept fixed or the base stock adjustment is postponed to the contract expiration time. We find that the initial demand rate, contract expiration time, and size of the drop in demand rate are the three key parameters driving the choice between the single‐adjustment policy and its special cases.     

How Much Uncertainty is Too Much and How Do We Know? A Case Example of the Assessment of Ozone Monitor Network Options

Limited time and resources usually characterize environmental decision making at policy organizations such as the U.S. Environmental Protection Agency. In these climates, addressing uncertainty, usually considered a flaw in scientific analyses, is often avoided. However, ignoring uncertainties can result in unpleasant policy surprises. Furthermore, it is important for decisionmakers to know how defensible a chosen policy option is over other options when the uncertainties of the data are considered. The purpose of this article is to suggest an approach that is unique from other approaches in that it considers uncertainty in two specific ways-the uncertainty of stakeholder values within a particular decision context and data uncertainty in the light of the decision-contextual data-values relationship. It is the premise of this article that the interaction between data and stakeholder values is critical to how the decision options are viewed and determines the effect of data uncertainty on the relative acceptability of the decision options, making the understanding of this interaction important to decisionmakers and other stakeholders. This approach utilizes the recently developed decision analysis framework and process, multi-criteria integrated resource assessment (MIRA). This article will specifically address how MIRA can be used to help decisionmakers better understand the importance of uncertainty on the specific (i.e., decision contextual) environmental policy options that they are deliberating.     

Near-optimal control policy for loss networks

In this paper, the phenomenon of the optimal management of requests of service in general networks is formulated as a control problem for a finite number of multiserver loss queues with Markovian routing. This type of problem may arise in a wide range of fields, e.g., manufacturing industries, storage facilities, computer networks, and communication systems. Using inductive approach of dynamic programming, the optimal admission control can be induced to be the functions of the number of requested service in progress. However, for large-scale network, the computational burden to find optimal control policy may be infeasible due to its involvement of the states for all stations in the networks. Hence, the idea of bottleneck modeling is borrowed to compute the near-optimal admission control policy. We reduced the scale of loss network and decreased the difference between the original and reduced models by making compensation for system parameters. A novel method is proposed in this paper to compute the compensation. Numerical results show that the near-optimal control policy demonstrates close performance to the optimal policy.     

Unemployment Benefits and Employment Policies in the Presence of a Strong Trade Union: A Comparison

Abstract. The paper analyses, within a game theoretic approach, the consequences on private employment and real wages of a government policy of raising unemployment benefits following a fall in employment. The effects of such a policy are then compared with those arising from a more conventional demand policy. Under the policy regime described the reaction of the unions will cause, when the economy is hit by a negative shock on employment, a tendency for the real wage to rise and for private employment to decrease further. As far as the comparison of such policy with a policy of direct employment by the government is concerned we have reached the following conclusions. A policy based on unemployment benefit will give rise to a smaller increase in the real wage than a policy based on public employment if the change in the marginal utility of being employed due to change in the unemployment benefit is smaller than the utility that the union will obtain from an extra employed person. Moreover it appears that a policy based on unemployment benefits has a smaller negative effect on private employment, than a policy based on direct employment. if such a policy is adopted just after an employment benefits represent also a subsidy to the firms. We have shown that the effects on the real wage of the Policy rule considered are in this case stronger. The effects on employment depend on the relative strength of the union reaction and of the policy's supply side effects.     

A reinforcement-learning approach for admission control in distributed network service systems

In the distributed network service systems such as streaming-media systems and resource-sharing systems with multiple service nodes, admission control (AC) technology is an essential way to enhance performance. Model-based optimization approaches are good ways to be applied to analyze and solve the optimal AC policy. However, due to “the curse of dimensionality”, computing such policy for practical systems is a rather difficult task. In this paper, we consider a general model of the distributed network service systems, and address the problem of designing an optimal AC policy. An analytical model is presented for the system with fixed parameters based on semi-Markov decision process (SMDP). We design an event-driven AC policy, and the stationary randomized policy is taken as the policy structure. To solve the SMDP, both the state aggregation approach and the reinforcement-learning (RL) method with online policy optimization algorithm are applied. Then, we extend the problem by considering the system with time-varying parameters, where the arrival rates of requests at each service node may change over time. In view of this situation, an AC policy switching mechanism is presented. This mechanism allows the system to decide whether to adjust its AC policy according to the policy switching rule. And in order to maximize the gain of system, that is, to obtain the optimal AC policy switching rule, another RL-based algorithm is applied. To assess the effectiveness of SMDP-based AC policy and policy switching mechanism for the system, numerical experiments are presented. We compare the performance of optimal policies obtained by the solutions of proposed methods with other classical AC policies. The simulation results illustrate that higher performance and computational efficiency could be achieved by using the SMDP model and RL-based algorithms proposed in this paper.     

A Nonatomic‐Game Approach to Dynamic Pricing under Competition

We study a revenue management problem involving competing firms. We assume the presence of a continuum of infinitesimal firms where no individual firm has any discernable influence over the evolution of the overall market condition. Under this nonatomic‐game approach, the unanimous adoption of an equilibrium pricing policy by all firms will yield a market‐condition process that in turn will elicit the said policy as one of the best individual responses. For both deterministic‐ and stochastic‐demand cases, we show the existence of equilibrium pricing policies that exhibit well‐behaving monotone trends. Our computational study reveals many useful insights, including the fact that only a reasonable number of firms are needed for our approach to produce near‐rational pricing policies.