考虑空间随机需求的急救站点选址规划

随着人民生活水平的提高和人口老龄化加剧，公众对急救医疗服务的要求越来越高。为保证急救需求的响应及时性，急救站点的选址规划问题受到广泛关注。急救站点选址的依据是需求的分布，然而现有研究未能充分考虑急救需求在空间分布上的随机性影响，通常将其空间分布简化为若干个集中需求点，或将规划空间划分为若干矩形网格，然而这种需求刻画过于粗略，导致需求覆盖水平的计算不够准确，影响配置方案的有效性。针对该问题，本研究应用高斯混合模型解决了急救需求的空间分布刻画问题，创新性地提出基于高斯混合聚类的站点选址规划方法，考虑急救需求时空随机性，建立了相应的机会约束规划模型。实际数据的验证分析表明，该选址方法能够显著减少服务延误时间和次数，保证急救服务的响应及时性。     

Hierarchical production planning for multi-product lines in the beverage industry¶

Multi-commodity production and distribution scheduling is one of the most complex and crucial problems facing many manufacturing companies. For a major European manufacturer specialising in bottling juices and drinks, we have designed and developed a hierarchical decomposition approach to the solution of the multi-commodity production planning problem. In this paper we focus our attention on the coarsest decomposition level, called multi-commodity aggregate production planning (MCAP). It concerns the choice of the best feasible production plan for a set of products (commodities) over an extended time horizon so as to meet forecast aggregate demands throughout the horizon. At this level, the problem constraints include hard constraints (such as production lines having a maximum capacity and products having short life-times), and soft constraints (budgetary concerns.) The objective is to determine the production plan that covers each period's demands as best as possible, while minimizing all relevant costs. Our method for solving MCAP produces optimal plans in negligible times in commodity PC workstations.     

PRODUCTION-DISTRIBUTION PLANNING IN A LARGE SCALE COMMODITY PROCESSING NETWORK

This paper describes a methodology for production-distribution planning in a large scale commodity processing network. Based on earlier research efforts dealing with single-commodity and multi-commodity distribution system modeling and on production planning for a single-plant commodity processing facility, a mathematical programming methodology is developed for a multiplant soybean processing network. Application of the model leads to the specification of a production plan for a multi-period time horizon, while at the same time indicating the quantities of soybean meal and soybean oil to be supplied to various customers in various locales. Both sets of decisions are made under the general criterion of maximizing the net income produced by the soybean processing complex, subject to various production, inventory, capacity, supply and demand constraints. Test results from application of the model are presented and discussed.     

A Hierarchical Product Development Planning Framework

Uncertainty in new product development (NPD) planning embraces market, creative, technological, and process dimensions to a much greater extent than in non‐NPD project planning. Yet, NPD management is becoming increasingly decentralized, both within the firm and across the supply chain. Hence, planning for NPD uncertainty often results in path‐dependent scenarios cutting across the strategic, tactical, and operational levels of planning. To coordinate this resulting complexity, we propose a stochastic hierarchical product development planning framework with multiple recourses, i. e., corrective actions, to maximize performance across a firm's entire NPD program. We also argue the necessity for a fourth planning level, the infrastructural, that reestablishes norms for market projections, technological forecasts, scheduling, and requirements as latent uncertainty in the environment is continually revealed. An illustration from the automotive industry is presented to demonstrate a deployment of our framework. We additionally discuss the applicability of this framework for managing NPD capabilities over time.     

Strategic supply network planning with vendor selection under consideration of risk and demand uncertainty

We present a stochastic version of a three-layer supply network planning problem that includes the selection of vendors that must be equipped with company-specific tools. The configuration of a supply network must be determined by using demand forecasts for a long planning horizon to meet a given service level. The risk induced by the uncertain demand is explicitly considered by incorporating the conditional value at risk. The objective is to maximize the weighted sum of the expected net present value of discounted cash flows and the conditional value at risk. This would lead to a non-linear model formulation that is approximated by a mixed-integer linear model. This approximation is realized by a piecewise linearization of the expected backlogs and physical inventory as non-linear functions of cumulative production quantities. A two-stage stochastic programming approach is proposed. Our numerical analysis of generic test instances indicates that solving the linearized model formulation yields a robust and stable supply network configuration when demand is uncertain.     

Bridging the Healthcare Access Divide: A Strategic Planning Model for Rural Telemedicine Network

Balancing access to healthcare and sustaining operational efficiency is a major issue in strategic planning of rural healthcare delivery systems. In this regard, telemedicine is being adopted as a versatile and low cost mechanism for delivering rural healthcare. This article presents a strategic planning model that incorporates different operational and service elements of the rural telemedicine healthcare network. Real‐world data from the rural Black‐belt region in the United States are used in a case study. A novel statistical approach based on decision trees and logistic regression is used to estimate demand of healthcare at the county level. Key issues such as the location of telemedicine health centers, coverage of health services, configuration of medical equipment, and patient travel policies are explored in light of patient demographics, scale of health coverage, and disease prevalence patterns. Results indicate that telemedicine networks can effectively improve healthcare services in rural areas with requisite operational efficiency.     

Planning a sustainable reverse logistics system: Balancing costs with environmental and social concerns

The present work aims to support tactical and operational planning decisions of reverse logistics systems while considering economic, environmental and social objectives. In the literature, when addressing such systems economic aspects have been often used, while environmental concerns have emerged only recently. The social component is the one less studied and rarely the combination of the three concerns has been analyzed. This work considers the three objectives and was motivated by the challenge of supporting decision makers when managing a real case study of a recyclable waste collection system, where strategic decisions on the number and location of depots, vehicles and containers were taken beforehand. Tactical and operational decisions are studied involving the establishment of service areas for each depot and the definition and scheduling of collection routes for each vehicle. Such decisions should represent a compromise solution between the three objectives translating a sustainable reverse logistics plan. The problem is modeled as a multi-objective, multi-depot periodic vehicle routing problem with inter-depot routes. A mathematical formulation and a solution approach are proposed. An approximation to the Pareto front is obtained for the case study and the trade-offs between the objectives are discussed. A balanced solution is proposed.     

An Integrated Decision Methodology for Designing and Operating an Air‐Express Courier's Distribution Network*

DHL, an international air‐express courier, has been operating in Hong Kong for many years. In 1998, the new international airport located at a site considerably distant from the old location opened in Hong Kong (HK). Other airport‐related infrastructure facilities have also been developed or are being developed, resulting in major changes in transport structure as well as a shift in customer demand. In this paper a multiyear distribution network is designed for DHL(HK) using an integrated network design methodology, which consists of a macro model and a micro model. The macro model, a mixed 0–1 LP, determines in an aggregate manner the least‐cost distribution network. The micro model, a simulation, evaluates the operational viability and efficacy of the network according to its service coverage and service reliability. We also illustrate how coverage and reliability can be improved via the integrated use of the two models. Extensive discussion on relevant planning and operational issues of an air‐express courier are included. The methodology has been successfully implemented at DHL(HK). It has been used to design the network, to test strategic decisions, and to update the network.     

A Simulation Metamodel for Response-Time Planning*

Field service management continues to be a major challenge for many service organizations as companies are required to provide more service with less resources. Especially in information intense environments, short response times for service calls are essential to avoid disruptions to a business office or production facility. Managers must regularly assess their manpower needs, and ensure that their allocation and operational decisions lead to the best service at the lowest cost. Xerox Corporation provides copiers, duplicators, and printing systems to an international market. Xerox operates a service network consisting of over 30,000 trained service personnel, each allocated to service regions by the service planning staff. Response-time planning involves many challenging problems: requirements planning at the national level, allocation planning at the district level, and operational planning at the team level. Customer service is critical and is commonly measured by response time—the time that elapses from when a service call is placed to when a service engineer begins service. This paper discusses how Xerox Corporation has used simulation models and metamodels to improve response-time planning and field service operations.     

Stochastic Measures of Network Resilience: Applications to Waterway Commodity Flows

Given the ubiquitous nature of infrastructure networks in today's society, there is a global need to understand, quantify, and plan for the resilience of these networks to disruptions. This work defines network resilience along dimensions of reliability, vulnerability, survivability, and recoverability, and quantifies network resilience as a function of component and network performance. The treatment of vulnerability and recoverability as random variables leads to stochastic measures of resilience, including time to total system restoration, time to full system service resilience, and time to a specific α% resilience. Ultimately, a means to optimize network resilience strategies is discussed, primarily through an adaption of the Copeland Score for nonparametric stochastic ranking. The measures of resilience and optimization techniques are applied to inland waterway networks, an important mode in the larger multimodal transportation network upon which we rely for the flow of commodities. We provide a case study analyzing and planning for the resilience of commodity flows along the Mississippi River Navigation System to illustrate the usefulness of the proposed metrics.     

A visual planning solution to streamline the processes of hybrid cross-dockings

Cross-docking is a logistic strategy widely adopted both in manufacturing and distribution contexts. Despite the huge number of researches on this topic, most of them remain rather theoretical as they do not pay enough attention to operational aspects and daily functioning patterns of cross-dockings. This article aims at introducing a new focus for cross-docking research by proposing a visual planning solution to manage daily operation of a manufacturing cross-docking. By avoiding complex optimization algorithms and by adopting concepts belonging to the lean management theory, the article shows the potential of visual planning techniques to improve performance of cross-dockings. Starting from a specific industrial context, the shipping warehouse of an Italian company of the oil andand gas sector, a visual management methodology has been proposed to support the operation of cross-dockings. Although developed in a particular context, the proposed methodology and its underlying principles are to be considered general and potentially applicable to a wide range of cross-dockings. The methodology fully exploits an analytical tool, namely, the Safety Margin coefficientthat could be used for capacity planning purposes and to evaluate quantitatively the system performance at a given time instant.     

Optimizing trains movement on a railway network

Focusing on solving critically important train operation problems on a railway network, this paper investigates a mathematical model for finding optimal trains movements under the consideration of operational interactions. With the predetermined routing and traversing order plan, we explicitly consider the optimization of energy consumption and travel time as the objective based on the coasting control methods. To reduce the calculation difficulties, simulation-based methodologies are proposed to compute the energy consumption and traversing time through using specific performance of the involved trains. A genetic algorithm integrated with simulation is designed to seek the approximate optimal coasting control strategies on the railway network. The numerical experiments investigate the effectiveness of the proposed model and algorithm.     

高速铁路客运网络列车开行方案优化模型

本文在分析铁路旅客列车开行方案优化研究进展的基础上,提出了一个适合我国铁路客运网络的开行方案优化模型。本模型综合考虑客票收入、运营成本、直达旅客数和总运送旅客数,在保证铁路旅客运输公共服务性质的基础上以运营商收益最大化为目标,对全网列车的开行方案的进行优化。利用随机生成数据进行的模型试验表明,模型可以在较短的时间内求解较大规模的铁路网络列车开行方案优化问题。     

AN APPLICATION OF MATERIAL REQUIREMENTS PLANNING TO HIGHER EDUCATION

Material requirements planning (MRP), a comprehensive planning and control technique based upon the dependent demand principle, enables manufacturing organizations to provide better customer service, reduce inventory investment, and increase resource utilization. This paper extends the dependent demand principle to the service sector and thus provides the basis for applying MRP to higher education. In the short run, administrators can schedule the necessary number of required courses and load each course based on student priorities to provide increased customer (i.e., student) service and faculty utilization. In the long run, course enrollment forecasts can be utilized by administrators to plan and control changes in faculty resources across departments and schools.     

Production planning of mixed-model assembly lines: a heuristic mixed integer programming based approach

Process technology capabilities are becoming increasingly important as flexible manufacturing continues to be more prevalent, and as competition compels companies to provide expanded variety, at ever lower cost, so introducing plant and processes technological constraints. Model flexibility can also benefit from an appropriate production planning process, especially concerning mixed-model assembly lines, since it can facilitate master scheduling and line balancing activities, which are essential aspects of flexibility. Robust and practical planning approaches have to take into account two different aspects: the first consists in ensuring that the elaborated aggregate plan can be disaggregated into at least one detailed feasible plan for the realised demand, whereas the second in ensuring that this detailed plan is feasible at the operational level. This article faces the model flexibility challenge, reviewing and discussing the planning problem of a real world assembly manufacturing system, producing high volume and a variety of agricultural tractors and machines, analysing and resolving some important issues related to technological, organisational and managerial constraints. This article illustrates the implementation of an Advanced Planning System integrated with a mixed integer-programming model, which is solved by a new iterative heuristic approach capable of achieving interesting planning improvements for model-flexibility management.     

Credibility-based rescheduling model in a double-track railway network: a fuzzy reliable optimization approach

Using a space–time network to represent the choice of train trajectories, this paper proposes a fuzzy optimization framework to reschedule trains in a double-track railway network when the capacity reduction is caused by a low-probability incident. We explicitly introduce a fuzzy variable-based recovery time to capture the uncertainty of incident duration based on professional judgements or empirical estimates. The problem is then formulated as a credibilistic two-stage fuzzy 0–1 integer optimization model to find a reliable operational plan for emergency response guidance. The first stage of the model aims to generate a traversing order on the incident link, and meanwhile the second stage adaptively generates optimized schedules to evaluate the operational plan. Crisp equivalents of mathematical models are further investigated to simplify solution methodologies. The numerical experiments, which are solved by using the GAMS optimization software, demonstrate the effectiveness and efficiency of the proposed approaches.     

A computerized financial planning model for a health maintenance organization

The time and resource costs needed to plan and start a prepaid medical program or health maintenance organization (HMO) are extensive. It can take up to 3 years to bring one on line and another 3 to 4 years to reach financial stability. Depending on the type of prepaid medical plan designed, the cost can reach $6 to $8 million before breakeven occurs. Because the financial stakes are so high, a systematic and sound business approach must be taken to find that one ‘best’ design that will survive in the market place. Thousands of hours are required to study all of the possible HMO design configurations. This paper describes how a corporation constructed a computerized financial planning model to simulate the financial behavior of a prepaid medical program with different organizational formats, operational policies and pricing and compensation schemes in varying market, economic and cost environments. Model development and application was a corporate affair. The computerized model provided a special design team with the capability to evaluate the economic impact of many different designs by asking ‘what if’ questions dealing with several key design and operating variables concerning different health benefit options, service utilization rates, staffing patterns, inflation rates and price and premium schedules. Thousands of hours of design time were saved and the corporation was able to find the ‘best’ possible design in a reasonable time and at a reasonable cost.     

考虑服务约束的第三方仓库收益与设计优化模型

第三方仓库作为服务提供商, 主要以期望收益最大化为目标, 但是必须满足一定的顾客服务标准。针对高需求环境, 考虑顾客服务水平约束, 提出了一个基于排队论的随机设计优化模型以使仓库的期望收益最大化。采用动态优化算法对模型求解, 选取实例进行了数值实验。结果显示, 模型的优化设计显著地提高了高需求环境下该第三方仓库的期望收益。在此基础上, 找到了服务约束的可行范围和有效范围, 为决策者制定服务标准提供了依据。     

一种策略层项目计划的双目标优化方法

针对产品开发项目管理的实际情况,对策略层计划优化方法进行研究。以工作包的工作量估算为基础,以资源投入水平和工期最小化为目标,考虑各种约束条件,提出一种策略层项目计划问题的混合整数规划问题模型。以非支配遗传算法NSGA-II为基础框架,设计了一种改进的双目标遗传算法。该算法针对问题的特点,提出了基于资源平滑的解码算法。参考NSGA-III的关键特征,对拥挤密度计算方法进行改进。通过企业实际项目案例,验证了算法的性能和所提出的策略层项目计划方法的有效性。     

Tactical coordination in a multi-location and multi-stage operations structure: A model and a pharmaceutical company case

In this paper, we look at the internal supply chain of an internationally operating firm characterized by a multi-location and multi-stage operations structure. We address problems at three levels, namely the strategic, tactical, and operational levels. Our approach goes beyond the operational literature, and focuses primarily on the tactical level. We specify a model and a case that capture strategic and tactical issues and relate the tactical issues to organizational issues. We simulate coordination in different organizational forms pertaining to the ‘tactical control’ of the firm. Our analysis suggests that a functionally organized multi-location and multi-stage operations structure using traditional planning will not work. The choice is between a strongly IT-based, centralized organization or a more decentralized organization using transfer prices as the coordination device.