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AbstractPeople often use cognitive and affective heuristics when judging the likelihood of a health outcome and making health decisions. However, little research has examined how heuristics shape risk perceptions and behavior among people who make decisions on behalf of another person. We examined associations between heuristic cues and caregivers' perceptions of their child's asthma risk, the frequency of caregivers' asthma management behaviors, and child health outcomes. We used Ipsos KnowledgePanel to recruit 814 U.S. adult caregivers of children with asthma of the age <18 years. Participants completed a survey at baseline (T1) and 3 months later (T2). Caregivers who, at T1, reported greater negative affect about their child's asthma (affect heuristic cue), greater ease of imagining their child experiencing asthma symptoms (availability heuristic cue), and greater perceived similarity between their child and a child who has ever experienced asthma symptoms (representativeness heuristic cue) reported statistically significantly (p < 0.05) higher interpersonal perceived risk of their child having an exacerbation or uncontrolled asthma at T1. They also indicated at T2 that their child had poorer asthma control and more frequent exacerbations. Greater T1 negative affect was associated with more frequent T2 actions to reduce inflammation, manage triggers, and manage symptoms, and with poorer T2 child health outcomes. Heuristic cues are likely important for interpersonal—not just personal—risk perceptions. However, the interrelationship between caregivers' ratings of heuristic cues (in particular, negative affect) and risk judgments may signify a struggle with managing their child's asthma and need for extra support from health care providers or systems.

Heuristic Approach to Inventory Control with Advance Capacity Information
There is a growing trend of information sharing within modern supply chains. This trend is mainly stimulated by recent developments in information technology and the increasing awareness that accurate and timely information helps firms cope with volatile and uncertain business conditions. We model a periodic-review, single-item, capacitated stochastic inventory system, where a supply chain member has the ability to obtain advance capacity information ('ACI') about future supply capacity availability. ACI is used to reduce the uncertainty of future supply and thus enables the decision-maker to make better ordering decisions. We develop an easily applicable heuristic based on insights gained from an analysis of the optimal policy. In a numerical study we quantify the benefits of ACI and compare the performance of the proposed heuristic with the optimal performance. We illustrate the conditions in which the procedure is working well and comment on its practical applicability.

AbstractIn this paper we study the scheduling problem that considers both production and job delivery at the same time with machine availability considerations. Only one vehicle is available to deliver jobs in a fixed transportation time to a distribution center. The vehicle can load at most K jobs as a delivery batch in one shipment due to the vehicle capacity constraint. The objective is to minimize the arrival time of the last delivery batch to the distribution center. Since machines may not always be available over the production period in real life due to preventive maintenance, we incorporate machine availability into the models. Three scenarios of the problem are studied. For the problem in which the jobs are processed on a single machine and the jobs interrupted by the unavailable machine interval are resumable, we provide a polynomial algorithm to solve the problem optimally. For the problem in which the jobs are processed on a single machine and the interrupted jobs are nonresumable, we first show that the problem is NP‐hard. We then propose a heuristic with a worst‐case error bound of 1/2 and show that the bound is tight. For the problem in which the jobs are processed on either one of two parallel machines, where only one machine has an unavailable interval and the interrupted jobs are resumable, we propose a heuristic with a worst‐case error bound of 2/3. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007

AbstractThis research investigates principles of judgmental heuristics and dual processing systems in the online purchasing environment. It examines the effects of availability cues in restaurant reviews on dining intentions and menu item choice. Two experiments are reported in which consumers make dining out and food choice decisions using simulated online review sites. The first experiment evaluates primacy–recency effects of positive and negative reviews along with different review types. The findings indicate that text plus ratings produce higher visit intentions and expectations compared with either cue by itself. The second experiment examines the effects of rating format, visual cues, and review valence on menu item choice. Pictures increase likelihood to choose a positively reviewed menu item but do not influence likelihood to choose a negatively reviewed item. This finding supports the negativity bias, whereby consumers place more weight on negative versus positive information. Consumers are more likely to choose a menu item with pictures when ratings are in numerical versus star rating format. The findings can be interpreted in terms of System 1 (heuristic) and System 2 (systematic) processing.

AbstractOne way of achieving the increased levels of system reliability and availability demanded by critical computer‐based control systems is through the use of fault‐tolerant distributed computer systems. This article addresses the problem of allocating a set of m tasks among a set of n processors in a manner that will satisfy various task assignment, system capacity, and task scheduling constraints while balancing the workload across processors. We discuss problem background, problem formulation, and a known heuristic procedure for the problem. A new solution‐improving heuristic procedure is introduced, and computational experience with the heuristics is presented. With only a modest increase in the amount of computational effort, the new procedure is demonstrated to improve dramatically solution quality as well as obtain near‐optimal solutions to the test problems.

Results of past research suggest that affect plays an important role in risk perception. Because affect may also increase the availability of risks, affect and availability are closely related concepts. Three studies tested the hypothesis that evoking negative affect (fear), either through past experience or through experimental manipulation, results in greater perceived risk. The present research focused on perception of flooding risk. Study 1 and Study 2 showed that participants who received risk information concerning a longer time period (e.g., 30 years) perceived more danger compared with participants who received risk information for one year. Study 2 showed that the interpretation of risk information was influenced by participants' own experiences with flooding. In Study 3, affect was experimentally manipulated. After looking at photographs depicting houses in a flooded region, participants perceived greater risk compared with participants in a control group. Taken together, the results of these three studies suggest that affect is important for successful risk communication. Results of the present research are in line with the affect heuristic proposed by Slovic and colleagues.

ABSTRACTThis paper presents a tractable set of integer programming models for the days‐off scheduling of a mix of full‐ and part‐time employees working α to β days/week (cycle) in a multiple‐objective, multiple‐location environment. Previous models were formulated to specifically schedule part‐time employees working either two or three days per week. These models were intractable because they required complete employee schedule information. The new models are deemed implicit optimal since they are required to supply only essential information. While the number of variables in previous models is an exponential increasing function of β‐α, the size of three of the new models is independent of α and β.The first three models developed here (as in [18]) deal with the trade‐offs between idle time, the number of employees required to work at multiple "locations," and the size of the total labor pool. The inherent flexibility of the implicit modeling approach is illustrated by the presentation of various modifications of the basic models. These modifications permit the use of preference weights on the number of employee work days/week (cycle) or the minimization of payroll costs where differential pay rates exist. These latter models may also be formulated such that idle time is ignored, constrained or minimized.The execution time for the implicit models (on a CDC CYBER 730 computer with commercially available software) averaged well under five seconds on 1200 trial problems for the type of application considered in [18]. A solution was obtained in less than 46 seconds of CPU time for a trial problem which would have required over 1.4 million integer variables with previous models.The availability of optimal solutions was invaluable in the development of two heuristics designed to deal with the trade‐offs of [16]. In an experimental analysis a previous heuristic produced results which averaged from 74 to 508 percent above optimum across six experimental conditions. The comparable new heuristic produced results which averaged from 3 to 8 percent above optimum for the same experimental conditions.The paper concludes by developing a framework to integrate the results of this research with the tour scheduling problem and by identifying several other areas for related research.

AbstractFlooding is one of the most significant natural disasters worldwide. Nevertheless, voluntary take‐up of individual damage reduction measures is low. A potential explanation is that flood risk perceptions of individual homeowners are below objective estimates of flood risk, which may imply that they underestimate the flood risk and the damage that can be avoided by damage reduction measures. The aim of this article is to assess possible flood risk misperceptions of floodplain residents in the Netherlands, and to offer insights into factors that are related with under‐ or overestimation of perceived flood risk. We analyzed survey data of 1,848 homeowners in the Dutch river delta and examine how perceptions of flood probability and damage relate to objective risk assessments, such as safety standards of dikes, as well as heuristics, including the availability heuristic and the affect heuristic. Results show that many Dutch floodplain inhabitants significantly overestimate the probability, but underestimate the maximum expected water level of a flood. We further observe that many respondents apply the availability heuristic.

Multi-access Edge Computing (MEC) is gaining momentum as it is considered as one of the enablers of 5G ultra-Reliable Low-Latency Communications (uRLLC) services. MEC deploys computation resources close to the end user, enabling to reduce drastically the end-to-end latency. ETSI has recently leveraged the MEC architecture to run all MEC entities, including MEC applications, as Virtual Network Functions (VNF) in a Network Functions Virtualization (NFV) environment. This evolution allows taking advantage of the mature architecture and the enabling tools of NFV, including the potential to apply a variety of service-tailored function placement algorithms. However, the latter need to be carefully designed in case of MEC applications such as uRLLC, where service access latency is critical. In this paper, we propose a novel placement scheme applicable to a MEC in NFV environment. In particular, we propose a formulation of the problem of VNF placement tailored to uRLLC as an optimization problem of two conflicting objectives, namely minimizing access latency and maximizing service availability. To deal with the complexity of the problem, we propose a Genetic Algorithm to solve it, which we compare with a CPLEX implementation of our model. Our numerical results show that our heuristic algorithm runs efficiently and produces solutions that approximate well the optimal, reducing latency and providing a highly-available service. ; This work has been partially supported by the European Union's H2020 5G-Transformer Project (grant no. 761536)

In this article, we set ourselves a task to test institutional memory hypothesis as a core of endogenous credit cycles. According to this hypothesis, risks taken by creditors depend largely on availability heuristic and experience of loan officers. To assess validity of this hypothesis we construct and estimate a simple VAR model. The data for this model is acquired from results of an experimental study (lasted for 70 rounds), the purpose of which is to identify behavioral patterns of participants while meeting demand for credit, specifics of subjectively weighted assessment of credit risk, based on shock approach. The results of the study allow confirming institutional memory hypothesis. After initial shock of bad debts, number of periods to recover willingness to accept risk has increased by 39%, which supports the hypothesis of availability heuristic?s influence. However, with improvement of loan portfolio?s quality, willingness to take risk is restoring. In addition, we managed to confirm existence of risk?s underestimation and overestimation periods in an experimental manner.

ABSTRACTThe dual problem of work tour scheduling and task assignment involving workers who differ in their times of availability and task qualifications is examined in this paper. The problem is presented in the context of a fast food restaurant, but applies equally well to a diverse set of service operations. Developing a week‐long labor schedule is a nontrivial problem, in terms of complexity and importance, which a manager spends as much as a full workday solving.The primary scheduling objective (the manager's concern) is the minimization of overstaffing in the face of significant hourly and daily fluctuations in minimum staffing requirements. The secondary objective (the workers' concern) is the minimization of the sum of the squared differences between the number of work hours scheduled and the number targeted for each employee. Contributing to scheduling complexity are constraints on the structure of work tours, including minimum and maximum shift lengths and a maximum number of workdays.A goal programming formulation of a representative problem is shown to be too large, for all practical purposes, to be solved optimally. Existing heuristic procedures related to this research possess inherent limitations which render them inadequate for our purposes. Subsequently, we propose and demonstrate a computerized heuristic procedure capable of producing a labor schedule requiring at most minor refinement by a manager.