可加号的门诊预约能力分配问题

预约服务可以有效优化医院门诊就诊流程,针对我国患者预约意识不强和预约患者爽约率高的特点,本文研究患者需求量较高时可以增加号源的条件下,考虑加号和拒绝患者成本,以门诊收益期望最大为目标,匹配预约患者和现场挂号患者需求量的能力分配问题。证明了门诊收益期望函数的单峰性,给出了最优解满足的条件。通过大量数值实验分析不同参数对门诊能力分配方案的影响,结果表明两类患者需求量对能力分配方案有较大影响,可加号情况下能力分配方案对患者爽约更敏感。     

Sequencing and scheduling N customers for a stochastic server

In this paper, we study the problem of sequencing and scheduling N customers for a single-server system. The goal is to balance the expected customer flow times and the expected system completion time. Customers are scheduled to enter the system by appointments only and the service times are exponentially distributed with different rates. The optimization of such a system involves determining the customer service order (sequencing) and the interarrival times (scheduling). We show that the service order depends upon the order of service rates and the optimal schedule can be obtained by solving a set of nonlinear equations. Numerical examples are used to illustrate the method.     

Effective cancellation policy to reduce the negative impact of patient no-show

The problem of patient no-show in outpatient delivery systems has been a long recognized issue. The negative impacts include underutilized medical resources, increased healthcare costs, decreased access to care, and reduced clinic efficiency and provider productivity. Many clinics have cancellation policies of asking their patients to cancel 24 or 48?h in advance. However, there is no logical or mathematical basis for such a policy. The objective is to develop an effective cancellation policy that accounts for current no-show rates, the clinic's flow, and its fill rates to minimize the cost of patient wait time, physician idle time, and overtime. A simulation approach is presented to determine the hours required for patients to call in advance for cancelling appointments. The findings indicate that when fill rates are low and no-show probabilities are high, the time required for patients to cancel appointments needs to increase in order to achieve the goal of being cost-effective.     

考虑存在取消预约情形的门诊预约能力分配策略

在现实的门诊预约问题中,已经预约的患者在接收医疗服务之前,有可能取消先前的预约,这会对医院的收益造成负面影响,如何在考虑患者存在取消预约的情形下,设计合理有效的能力分配策略来保证医院的收益,是一个值得研究的问题.本文针对具有提前预约和当天预约的门诊预约能力分配问题,在考虑提前预约患者可能存在取消预约行为的情形下,提出了一种提前预约患者和当天预约患者的最优能力分配策略。文中首先以医院的期望收益最大作为决策目标,建立了存在取消预约患者的医疗预约问题的马尔科夫过程模型,并给出了该模型的相关性质;基于所建立模型的特征,证明了对于任意的提前预约时段,存在提前预约患者的最佳数量,进而给出了提前预约患者和当天预约患者的最优能力分配策略以及确定该策略的精确算法;最后,通过数值试验说明了本文所提出的能力分配策略的适用性和有效性。     

The application of reliability constrained stochastic capacity planning models to the service sector

Emphasis on quality management has recently permeated not only the manufacturing sector, but the service sector as well. Consequently, quality service and consumer satisfaction have become realities for many monopolistic service oriented industries facing competition. In order to effectively implement timely service within these industries (i) capacity plans must be developed which provide adequate staffing during both peakload and offpeak hours, as well as optimal (ii) prices and (iii) reliability of service. This paper builds on the results of Boronico (1992) in illustrating how reliability constrained marginal cost, within which optimal price is embodied, and minimum cost capacity plans may be determined for a service provider facing stochastic demand. Excess demand is not lost, but is deferred: a characteristic that typifies the operation of many delivery systems, such as postal services. Results indicate that marginal costs are convex with respect to reliability of service, while changes in the demand distribution's variability may impact optimal capacity by either increasing or decreasing required capacity.     

The risk and information sharing of application services supply chain

We study an application services supply chain consisting of one application service provider (ASP) and one application infrastructure provider (AIP). The AIP supplies the computer capacity to the ASP that in turn sells the value-added application services to the market. The market is characterized by a price-sensitive random demand. The ASP’s objective is to determine the optimal price of its service to the market and the optimal capacity to purchase from the AIP. The AIP’s goal on the other hand is to maximize its profit from selling the capacity to the ASP.     

Outpatient appointment scheduling given individual day-dependent no-show predictions

This paper examines the combined use of predictive analytics, optimization, and overbooking to schedule outpatient appointments in the presence of no-shows. We tackle the problem of optimally overbooking appointments given no-show predictions that depend on the individual appointment characteristics and on the appointment day. The goal is maximizing the number of patients seen while minimizing waiting time and overtime. Our analysis leads to the definition of a near-optimal and simple heuristic which consists of giving same-day appointments to likely shows and future-day appointments to likely no-shows. We validate our findings by performing extensive simulation tests based on an empirical data set of nearly fifty thousand appointments from a real outpatient clinic. The results suggest that our heuristic can lead to a substantial increase in performance and that it should be preferred to open access under most parameter configurations. Our paper will be of great interest to practitioners who want to improve their clinic performance by using individual no-show predictions to guide appointment scheduling.     

Service outsourcing under co-opetition and information asymmetry

Co-opetition refers to the phenomenon that firms simultaneously cooperate and compete in order to maximize their profits. This paper studies the contracting for an outsourcing supply chain (a user company vs. a service provider) in the presence of co-opetition and information asymmetry. The user company outsources part of his service capacity at a discount price to the service provider for sale. The service provider charges a commission for doing outsourcing work and competes with the user company for the service capacity to satisfy their respective demands. We solve for the service provider’s optimal commission decision and the user company’s optimal outsourcing decisions (outsourcing volume and price discount) when the user company has private information about his service capacity. Specifically, we highlight the following observations. For the service provider, a menu of two-part tariffs that consist of a fixed commission and a per-volume commission can reveal the true type of the user company’s capacity; the user company’s optimal outsourcing proportion is quasi-convex and the optimal price discount is non-decreasing in his capacity volume, which is counterintuitive.     

周期性需求的供应商配送排程优化研究

在供应商管理库存(VMI)模式中,从提高供应商服务水平的视角,研究零售商具有周期性需求,供应商采用直接配送策略情形下以最小化缺货损失为目标的供应商配送日程安排问题。根据零售商最大需求周期的特点,设计了R倍放大(RTE)策略,分别针对实际中的边际缺货损失费率、固定缺货损失费率和递增缺货损失费率,证明了RTE策略在配送周期满足不同条件下对应的近似比。通过近似比的比较和算例分析,发现RTE策略在边际缺货损失费率下表现最好,某些情形下可以达到最优。研究结果对面对周期性需求的供应商配送排程具有一定的指导意义。     

免疫算法在车辆调度问题中的应用

免疫算法是模仿生物体高度进化、复杂的免疫系统仿生的一种智能化启发式算法。本文根据车辆调度问题的具体情况，应用免疫算法解决车辆调度中路线安排问题，并提出了一种基于分组匹配的亲和力的计算方法。实验结果表明，免疫算法能有效地应用于车辆调度中路线安排问题。     

A stochastic approximation method for the single-leg revenue management problem with discrete demand distributions

We consider the problem of optimally allocating the seats on a single flight leg to the demands from multiple fare classes that arrive sequentially. It is well-known that the optimal policy for this problem is characterized by a set of protection levels. In this paper, we develop a new stochastic approximation method to compute the optimal protection levels under the assumption that the demand distributions are not known and we only have access to the samples from the demand distributions. The novel aspect of our method is that it works with the nonsmooth version of the problem where the capacity can only be allocated in integer quantities. We show that the sequence of protection levels generated by our method converges to a set of optimal protection levels with probability one. We discuss applications to the case where the demand information is censored by the seat availability. Computational experiments indicate that our method is especially advantageous when the total expected demand exceeds the capacity by a significant margin and we do not have good a priori estimates of the optimal protection levels.     

Economic lot scheduling with deliberated and controlled coproduction

This paper presents an algorithm to define the optimal parameters for deliberated and controlled coproduction in an economic lot scheduling problem setting (DCCELSP). Coproduction is said to be deliberated and controlled because it is possible to decide whether or not to coproduce when all the parameters associated with the process are known. The aim is to determine how to produce two products most economically where deliberated coproduction is an option. For this purpose, a procedure for defining optimal lot periods is introduced. Two models are proposed for this procedure and a numerical illustration is provided to gain insight into their dynamics. The cost advantages of coproduction were found to depend on the relationship between setup and holding costs, production rates, and demand for products. The more similar these system parameters are and the higher the machine usage ratio is, the more favourable coproduction is. Additionally, if coproduction is not deliberated appropriately, costs soar.     

The Common Cycle Economic Lot Scheduling Problem with Backorders: Benefits of Controllable Production Rates

In this paper, we deal with the production scheduling ofseveral products that are produced periodically, in a fixed sequence, ona single machine. In the literature, this problem is usually referred to asthe Common Cycle Economic Lot Scheduling Problem. We extend thelatter to allow the production rates to be controllable at the beginningof as well as during each production run of a product. Also, we assumethat unsatisfied demand is completely backordered. The objective is todetermine the optimal schedule that satisfies the demand for all theproducts and that realizes the minimum average setup, inventoryholding and backlog cost per unit time. Comparison with previousresults (when production rates are fixed) reveals that averagecosts can be reduced up to 66% by allowing controllable productionrates.     

A simulation study of scheduling clinic appointments in surgical care: individual surgeon <Emphasis Type="Italic">versus</Emphasis> pooled lists

The purpose of this paper is to compare two methods of scheduling outpatient clinic appointments in the setting where the availability of surgeons for appointments depends on other clinical activities. We used discrete-event simulation to evaluate the likely impact of the scheduling methods on the number of patients waiting for appointments, and the times to appointment and to surgery. The progression of individual patients in a surgical service was modelled as a series of updates in patient records in reaction to events generated by care delivery processes in an asynchronous fashion. We used the Statecharts visual formalism to define states and transitions within each care delivery process, based on detailed functional and behavioural specifications. Our results suggest that pooling referrals, so that clinic appointments are scheduled with the first available surgeon, has a differential impact on different segments of patient flow and across surgical priority groups.     

考虑衍生需求和粉丝效应的视频服务供应链质量努力策略研究

视频服务作为“互联网+”时代下的新型文化产业模式,日益受到人们的关注。本文构建一个视频服务平台和一个视频服务提供商组成的视频服务供应链,视频服务提供商通过视频服务平台向用户提供基础服务和两阶段衍生服务。考虑视频服务供应链成员的四种行为因素对服务需求的影响,并分别建立平台定价模式和提供商定价模式下服务供应链成员的利润函数,运用博弈理论,优化求解得到两种模式下服务供应链成员最优的质量努力策略和利润。最后,通过数值仿真,探讨了粉丝效应和收益分成比例与最优质量努力策略和最优利润的相关性,并得出相关结论,给出管理启示。     

The Optimality of the ‘Zero-Switch’ Rule for a Class of Economic Lot-Scheduling Problems

The economic lot-scheduling problem for the single-machine, n-item scheduling problem has received attention in a number of journals. One approach is to define a sequence (called the fundamental cycle) in which every item is made at least once, and then to determine the length of production runs consistent with the aggregate inventory level which will maximize the length of the cycle duration. The assumption that production is switched from one item to the next only when the inventory level of the latter reaches zero is often used in heuristic solutions to these models. This paper illustrates the conditions in which the ‘zero-switch’ rule is a necessary condition at the optimal solution for situations in which demand is continuous and production capacity equals aggregate demand.     

两种运输方式下的船只优化排序模型及算法

本文讨论的是在两种不同容量的船只和两条不同运输路线的情况下的库存与运输联合优化排序问题.传统的经济批量订货问题里每次定购成本固定不变,而我们的问题里面定购成本是阶跃式的,与使用的船数相关.以往运输网络优化的论文都只考虑一种容量的运输工具,没有考虑不同容量的运输工具.本文结合这两方面做了进一步的研究,并根据实际应用背景建立了数学模型,讨论最优解的性质,由最优解性质给出了复杂度为O(N4) 的多项式算法.     

A Note on Dave's Inventory Model for Deteriorating Items

In this paper an attempt has been made to generalise Dave's results on an inventory model for deteriorating items. He has derived the results for optimal order level and lot size, considering a deterministic constant demand throughout the scheduling period. Here, a variable known demand is taken to show that the optimality conditions for the optimal initial stock do not depend on the nature of the demand. A numerical example is used to illustrate the analysis.     

A decomposed branch-and-price procedure for integrating demand planning in personnel staffing problems

The personnel staffing problem calculates the required workforce size and is determined by constructing a baseline personnel roster that assigns personnel members to duties in order to cover certain staffing requirements. In this research, we incorporate the planning of the duty demand in the staff scheduling problem in order to lower the staffing costs. More specifically, the demand originates from a project scheduling problem with discrete time/resource trade-offs, which embodies additional flexibility as activities can be executed in different modes. In order to tackle this integrated problem, we propose a decomposed branch-and-price procedure. A tight lower and upper bound are calculated using a problem formulation that models the project scheduling constraints and the time-related resource scheduling constraints implicitly in the decision variables. Based upon these bounds, the strategic problem is decomposed into multiple tactical subproblems with a fixed workforce size and an optimal solution is searched for each subproblem via branch-and-price. Fixing the workforce size in a subproblem facilitates the definition of resource capacity cuts, which limit the set of eligible project schedules, decreasing the size of the branching tree. In addition, in order to find the optimal integer solution, we propose a specific search strategy based upon the lower bound and dedicated rules to branch upon the workload generated by a project schedule. The computational results show that applying the proposed search space decomposition and the inclusion of resource capacity cuts lead to a well-performing procedure outperforming different other heuristic and exact methodologies.     

Signalling effect of daily deal promotion for a start-up service provider

In this paper, we consider a start-up service provider that decides whether to advertise its service product by offering temporary daily deal promotion. Based on the repeat purchase mechanism, we show that both the commission rate (ie, the revenue-sharing ratio) charged by the daily deal site and the discount level offered by the service provider play important roles in signalling the initially unobservable quality level of the service provider. A high commission rate can facilitate the signalling of the daily deal promotion, and in equilibrium only the high-quality service provider would do daily deal promotion. We find that if the daily deal site adopts a two-part tariff charging scheme, the high-quality service provider can always signal its quality by offering daily deals. And the two-part tariff leads to a lower signalling cost but a higher repeat purchase rate than those under the revenue-sharing if the variable cost of the low-quality service provider is not too large.