Evrim Didem Güneş

Scheduling with tool changes to minimize total completion time: Basic results and SPT performance

Abstract We consider a single machine sequencing problem subject to tool wear, where the objective is to minimize the total completion time. We briefly describe the problem and discuss its properties, complexity and solution. Mainly, however, we focus on the performance of the SPT list-scheduling heuristic. We provide theoretical worst-case bounds on SPT performance and also demonstrate its empirical behavior.

Modeling Customer Reactions to Sales Attempts: If Cross-Selling Backfires

Cross-selling attempts, based on estimated purchase probabilities, are not guaranteed to succeed and such failed attempts may annoy customers. There is a general belief that cross-selling may backfire if not implemented cautiously, however, there is not a good understanding of the nature and impact of this negative reaction or appropriate policies to counter-balance it. This article focuses on this issue and develops a modeling framework that makes use of a Markov decision model to account for negative customer reactions to failed sales attempts and the effect of past contacts in managing cross-selling initiatives. Three models are analyzed, where purchase probabilities are affected from customer maturity, the number of failed attempts since the last purchase, or both. The analysis shows that customer reactions to cross-sell attempts make the purchase probabilities endogenous to the firm’s cross-selling decisions; hence, the optimal cross-selling policy becomes a function of customer state. The results highlight the role that the cost of excessive cross-selling (direct as well as in the form of customer reactions) plays in optimal policies. Cross-sell data from a retail bank illustrate in what context the modeling framework can be applied and underline the importance of customizing cross-sell policies to individual customers.

Value Creation in Service Delivery: Relating Market Segmentation, Incentives, and Operational Performance

This paper studies service-delivery design in settings where firms engage in value-creation activities that have the objective of generating additional revenue from customer interactions. The paper provides a general modelling framework to analyze the ties between market segmentation decisions, incentives, and process performance in such service-delivery systems. The firm is modelled as a single-server queue, in a principal-agent framework. Customers have different value-generation potentials whose realizations are observed by the server but not by the manager of the firm. The manager determines a market segmentation scheme given an overall customer value-generation profile, which divides customers into two groups (high and low), and also determines a service level for each segment. The server decides which of the two available service levels (high and low) to provide for each customer, given a compensation scheme offered by the manager. The optimal market segmentation decision, optimal service-level choice, and a set of optimal linear incentive contracts that enable their implementation are characterized. The robustness of these strategies is explored with respect to model parameters and assumptions. It is shown that a market segmentation scheme that combines revenue generation concerns with their process implications is essential for success. Characteristics of appropriate incentive schemes are identified.

Outpatient appointment scheduling in presence of seasonal walk-ins

This study investigates appointment systems (AS), as combinations of access rules and appointment-scheduling rules, explicitly designed for dealing with walk-in seasonality. In terms of ‘access rules’, strategies are tested for adjusting capacity through intra-week, or monthly seasonality of walk-ins, or their combined effects. In terms of ‘appointment rules’, strategies are tested to determine which particular slots to double-book or leave open in cases where seasonal walk-in rates exceed or fall short of the overall yearly rate. In that regard, this study integrates capacity and appointment decisions, which are usually addressed in an isolated manner in previous studies. Simulation optimization is used to derive heuristic solutions to the appointment-scheduling problem, and the findings are compared in terms of in-clinic measures of patient wait time, physician idle time and overtime. The goal is to provide practical guidelines for healthcare practitioners on how to best design their AS when seasonal walk-ins exist.

Matching patient and physician preferences in designing a primary care facility network

This paper introduces an integer programming model for planning primary care facility networks, which accounts for the interests of different stakeholders while maximizing access to health care. Physician allocation to health-care facilities is explicitly modelled, which allows consideration of physician incentives in the planning phase. An illustrative case study in the Turkish primary care system is presented to show the implications of focusing on patient or physician preferences in the planning phase. A discussion of trade-offs between the different stakeholder preferences and some recommendations for modelling choices to match these preferences are provided. In the context of this case, we found that using an access measure that decays with distance, and incorporating nearest allocation constraints improves performance for all stakeholders. We also show that increasing the number of physicians may have adverse affects on access measures when physician preferences are addressed.

Health Network Mergers and Hospital Re-Planning

This paper presents an integer programming formulation for the hospital re-planning problem which arises after hospital network mergers. The model finds the best re-allocation of resources among hospitals, the assignment of patients to hospitals and the service portfolio to minimize the system costs subject to quality and capacity constraints. An application in the Turkish hospital networks case is illustrated to show the implications of consolidation of health insurance funds on resource allocations and flow of patients in the system.

Transition to family practice in Turkey

INTRODUCTION Turkeys primary health care (PHC) system was established in the beginning of the 1960s and provides preventive and curative basic medical services to the population. This article describes the experience of the Turkish health system, as it tries to adapt to the European health system. It describes the current organization of primary health care and the family medicine model that is in the process of implementation and discusses implications of the transition for family physicians and the challenges faced in meeting the needs for health care staff. In Turkey a trend toward urbanization is evident and more staff positions in rural PHC centers are vacant. Shortages of physicians and an ineffective distribution of doctors are seen as a major problem. Family medicine gained popularity at the beginning of the 1990s, as a specialty with a 3-year postgraduate training program. Medical practitioners who are graduates of a 6-year medical training program and are already working in the PHC system are offered retraining courses. Better working conditions and higher salaries may be important incentives for medical practitioners to sign a contract with the social security institution of Turkey. DISCUSSION The lack of well-trained primary care staff is an ongoing challenge. Attempts to retrain medical practitioners to act as family physicians show promising results. Shortness of physician and health professionals and lack of time and resources in primary health care are problems to overcome during this process.

Location Problems in Healthcare

In this chapter, we discuss facility location problems arising in the context of healthcare. We concentrate on three main areas: the most classical one is healthcare facility location which is closely related to public facility location. Secondly, we look at ambulance planning which includes ambulance location and relocation problems. In the last part, we give an overview of hospital layout problems. For all three parts, we state some important models and give an overview of relevant literature as well as current research directions. A comprehensive reference list is included at the end of the chapter.

A Modeling Framework for Control of Preventive Services

We present a modeling framework for facilities that provide both screening (preventive) and diagnostic (repair) services. The facility operates in a random environment that represents the condition of the population that needs screening and diagnostic services, such as the disease prevalence level. We model the environment as a partially endogenous process: the population’s health can be improved by providing screening services, which reduces future demand for diagnostic services. We use event-based dynamic programming to build a framework for modeling different kinds of these facilities. This framework contains a number of service priority policies that are concerned with prioritizing screening versus diagnostic services. The main trade-off is between serving urgent diagnostic needs and providing screening services that may decrease future diagnostic needs. Under certain conditions, this trade-off reverses the famous cμ rule; i.e., the patients with lower waiting cost are given priority over the others. We define appropriate event operators and specify the properties preserved by these operators. These characterize the structure of optimal policies for all models that can be built within this framework. A numerical study on colonoscopy services illustrates how the framework can be used to gain insights on developing good screening policies.

Modeling time allocation for prevention in primary care

This paper discusses the problem of allocating time for prevention at the primary care level, focusing on a general practitioner (GP) practice. The basic trade-off is between improved state of the health of the population, which translates into less demand for the GP services, and a decreased capacity for curative services, which translates into increased congestion. The problem of how much time to devote to prevention is modeled as a non-linear optimization problem. As an extension of the problem, selection of preventive activities to perform among recommended alternatives is modeled using a knapsack formulation, and its application is illustrated with a numerical example.