Call Center Delay Announcement Using a Newsvendor‐Like Performance Criterion

The problem of estimating delays experienced by customers with different priorities, and the determination of the appropriate delay announcement to these customers, in a multi‐class call center with time varying parameters, abandonments, and retrials is considered. The system is approximately modeled as an M(t)/M/s(t) queue with priorities, thus ignoring some of the real features like abandonments and retrials. Two delay estimators are proposed and tested in a series of simulation experiments. Making use of actual state‐dependent waiting time data from this call center, the delay announcements from the estimated delay distributions that minimize a newsvendor‐like cost function are considered. The performance of these announcements is also compared to announcing the mean delay. We find that an Erlang distribution‐based estimator performs well for a range of different under‐announcement penalty to over‐announcement penalty ratios.     

Comparison of Subsidy Schemes for Reducing Waiting Times in Healthcare Systems

This study analyzes subsidy schemes that are widely used in reducing waiting times for public healthcare service. We assume that public healthcare service has no user fee but an observable delay, while private healthcare service has a fee but no delay. Patients in the public system are given a subsidy s to use private service if their waiting times exceed a pre‐determined threshold t. We call these subsidy schemes (s, t) policies. As two extreme cases, the (s, t) policy is called an unconditional subsidy scheme if t = 0, and a full subsidy scheme if s is equal to the private service fee. There is a fixed budget constraint so that a scheme with larger s has a larger t. We assess policies using two criteria: total patient cost and serviceability (i.e., the probability of meeting a waiting time target for public service). We prove analytically that, if patients are equally sensitive to delay, a scheme with a smaller subsidy outperforms one with a larger subsidy on both criteria. Thus, the unconditional scheme dominates all other policies. Using empirically derived parameter values from the Hong Kong Cataract Surgery Program, we then compare policies numerically when patients differ in delay sensitivity. Total patient cost is now unimodal in subsidy amount: the unconditional scheme still yields the lowest total patient cost, but the full subsidy scheme can outperform some intermediate policies. Serviceability is unimodal too, and the full subsidy scheme can outperform the unconditional scheme in serviceability when the waiting time target is long.     

Improving routing and scheduling decisions at a distributor of industrial gasses

This paper investigates cyclical inventory replenishment for a company's regional distribution center that supplies, distributes, and manages inventory of carbon dioxide (_CO2)$({\mathrm{CO}}_2)$ at over 900 separate customer sites in Indiana. The company previously experienced high labor costs with excessive overtime and maintained a regular back-log of customers experiencing stockouts. To address these issues we implemented a three-phase heuristic for the cyclical inventory routing problem encountered at one of the company's distribution centers. This heuristic determines regular routes for each of three available delivery vehicles over a 12-day delivery horizon while improving four primary performance measures: delivery labor cost, stockouts, delivery regularity, and driver–customer familiarity. It does so by first determining three sets of cities (one for each delivery vehicle) that must be delivered to each day based on customer requirements. Second, the heuristic assigns the remaining customers in other cities to one of the three “backbone routes” determined in phase 1. And third, it balances customer deliveries on each daily route over the schedule horizon. Through our methodology, we were able to significantly reduce overtime, driving time, and labor costs while improving customer service.     

The design of socially optimal decisions in a consensus scenario

Several situations of conflict between basic social principles can crop up during a consensus searching process. The majority principle and respect for minority groups is a possible example of a conflictive situation between two social principles. In this paper, we outline a specific consensus searching scenario, where individual preferences are expressed by “pairwise” comparison matrices. The set of compromise consensuses between the majority and minority principles is determined using a procedure based upon an adaptation of Yu's p-metric distances. Finally, we use three different theoretical approaches – utility theory, p-metric distance functions and bargaining theory – to obtain the social optimum from the set of compromise consensuses. The links and differences among the three approaches are analysed. Finally, the working of the proposed theoretical framework is illustrated with the help of a forestry case study.     

Modeling and Managing the Percentage of Satisfied Customers in Hidden and Revealed Waiting Line Systems

We perform an analysis of various queueing systems with an emphasis on estimating a single performance metric. This metric is defined to be the percentage of customers whose actual waiting time was less than their individual waiting time threshold. We label this metric the Percentage of Satisfied Customers (PSC.) This threshold is a reflection of the customers' expectation of a reasonable waiting time in the system given its current state. Cases in which no system state information is available to the customer are referred to as “hidden queues.” For such systems, the waiting time threshold is independent of the length of the waiting line, and it is randomly drawn from a distribution of threshold values for the customer population. The literature generally assumes that such thresholds are exponentially distributed. For these cases, we derive closed form expressions for our performance metric for a variety of possible service time distributions. We also relax this assumption for cases where service times are exponential and derive closed form results for a large class of threshold distributions. We analyze such queues for both single and multi‐server systems. We refer to cases in which customers may observe the length of the line as “revealed” queues.“ We perform a parallel analysis for both single and multi‐server revealed queues. The chief distinction is that for these cases, customers may develop threshold values that are dependent upon the number of customers in the system upon their arrival. The new perspective this paper brings to the modeling of the performance of waiting line systems allows us to rethink and suggest ways to enhance the effectiveness of various managerial options for improving the service quality and customer satisfaction of waiting line systems. We conclude with many useful insights on ways to improve customer satisfaction in waiting line situations that follow directly from our analysis.     

The facility location problem with Bernoulli demands

This paper presents the facility location problem with Bernoulli demands. In this capacitated discrete location stochastic problem the goal is to define an a priori solution for the locations of the facilities and for the allocation of customers to the operating facilities that minimizes the sum of the fixed costs of the open facilities plus the expected value of the recourse function. The problem is formulated as a two-stage stochastic program and two different recourse actions are considered. For each of them, a closed form is presented for the recourse function and a deterministic equivalent formulation is obtained for the case in which the probability of demand is the same for all customers. Numerical results from computational experiments are presented and analyzed.     

A heuristic to minimize total flow time in permutation flow shop

In this paper, we address an n-job, m-machine permutation flow shop scheduling problem for the objective of minimizing the total flow time. We propose a modification of the best-known method of Framinan and Leisten [An efficient constructive heuristic for flowtime minimization in permutation flow shops. Omega 2003;31:311–7] for this problem. We show, through computational experimentation, that this modification significantly improves its performance while not affecting its time-complexity.     

Applying consistent fuzzy preference relations to partnership selection

Partnership selection has been important to the formation of a virtual enterprise. Based on the fuzzy preference programming (FPP) method proposed by Mikhailov [Fuzzy analytical approach to partnership selection in formation of virtual enterprises. Omega 2002;30:393–401], this investigation presents a consistent fuzzy preference relations method to select partners. Human thoughts are full of uncertainty, so the decision-makers cannot make exact pairwise comparisons. The FPP method solves this problem using an interval value instead of Saaty's 1–9 scale. In this study, the FPP method is reviewed, and then the consistent fuzzy preference relations method is elucidated. Finally, the presented method is applied to the example addressed by Mikhailov [Fuzzy analytical approach to partnership selection in formation of virtual enterprises. Omega 2002;30:393–401]. This study reveals that the proposed method yields consistent decision rankings from only n-1$n-1$ pairwise comparisons—the same number as in Mikhailov's research. Briefly, the presented consistent fuzzy preference relations method is an easy and practical way to provide rankings of partnership in making decision.     

Two-stage time minimizing assignment problem

This paper deals with the optimal selection of m out of n facilities to first perform m   given primary jobs in Stage-I followed by the remaining (n-m)$(n-m)$ facilities performing optimally the (n-m)$(n-m)$ secondary jobs in Stage-II. It is assumed that in both the stages facilities perform in parallel. The aim of the proposed study is to find that set of m   facilities performing the primary jobs in Stage-I for which the sum of the overall completion times of jobs in Stage-I and the corresponding optimal completion time of the secondary jobs in Stage-II by the remaining (n-m)$(n-m)$ facilities is the minimum. The developed solution methodology involves solving the standard time minimizing and cost minimizing assignment problems alternately after forbidding some facility-job pairings and suggests a polynomially bound algorithm. This proposed algorithm has been implemented and tested on a variety of test problems and its performance is found to be quite satisfactory.     

A visual interactive approach to classical and mixed vehicle routing problems with backhauls

In this paper a new visual interactive approach for the classical vehicle routing problem with backhauls (VRPB) and its extensions is presented. The classical VRPB is the problem of designing minimum cost routes from a single depot to two type customers that are known as Backhaul (pickup) and Linehaul (delivery) customers where deliveries after pickups are not allowed. The mixed VRPB is an extension of the classical VRPB where deliveries after pickups are allowed.     

Revenue Management of Reusable Resources with Advanced Reservations

We consider a revenue management problem wherein the seller is endowed with a single type resource with a finite capacity and the resource can be repeatedly used to serve customers. There are multiple classes of customers arriving according to a multi‐class Poisson process. Each customer, upon arrival, submits a service request that specifies his service start time and end time. Our model allows customer advanced reservation times and services times in each class to be arbitrarily distributed and correlated. Upon arrival of each customer, the seller must instantaneously decide whether to accept this customer's service request. A customer whose request is denied leaves the system. A customer whose request is accepted is allocated with a specific item of the resource at his service start time. The resource unit occupied by a customer becomes available to other customers after serving this customer. The seller aims to design an admission control policy that maximizes her expected long‐run average revenue. We propose a policy called the ε‐perturbation class selection policy (ε‐CSP), based on the optimal solution in the fluid setting wherein customers are infinitesimal and customer arrival processes are deterministic, under the restriction that the seller can utilize at most (1 − ε) of her capacity for any ε ∈ (0, 1). We prove that the ε‐CSP is near‐optimal. More precisely, we develop an upper bound of the performance loss of the ε‐CSP relative to the seller's optimal revenue, and show that it converges to zero with a square‐root convergence rate in the asymptotic regime wherein the arrival rates and the capacity grow up proportionally and the capacity buffer level ε decays to zero.     

Evaluating time streams of income

When a decision maker considers possible returns from a business project or investment, he often faces the problem that these returns are not all received at the same time, and thus he must make some adjustments to take account of his time preference for money. After a review of discounting, a utility theory approach is made by developing a two-attribute utility function u(x, t) which represents the desirability of an income of x at a time t in the future. Assumptions to simplify the assessment of this function are considered. Then u(x, t) is used to form a criterion for evaluating infinite time streams of income.     

Performance of weather-conditional rebates under different risk preferences

Retailers who sell seasonal products often face challenges in demand management due to weather uncertainty. In many cases, they make their ordering and pricing decisions prior to the regular selling season but the vast majority of sales do not occur until after the season starts, during which unfavorable weather conditions may result in high monetary losses. To protect against such adverse financial outcomes, retailers may offer weather-linked promotions such as weather rebates and induce customers to make early purchases. Specifically, weather-conditional rebates are incentives offered in an advance promotional period to be paid to the early buyers if the weather state in the regular season is unfavorable. In the presence of seasonal weather uncertainty, risk attitudes of retailers and buyers may play an important role on the effectiveness of these promotions. In this paper, we analyze the performance of weather-conditional rebates by explicitly considering the impact of different risk behaviors. First, we study the case in which the retailer and customers are risk-neutral and show that the weather-conditional rebates are effective in increasing the retailer's profits. Under the assumption of the retailer's risk-neutrality, we conduct a simulation study to investigate the impact of customers' alternative early-purchase behaviors on the performance of the rebate program. Next, we consider a risk-averse retailer. We model the retailer's risk aversion primarily in the mean–variance framework and find that the rebate program can be designed to increase the mean profit and reduce the profit variance simultaneously. Furthermore, by combining the rebate program with a financial instrument such as binary weather options, the retailer can obtain greater benefits from weather-conditional rebates.     

Cha n nel assig nme n t problem a nd n-fold t-separa ted $$L(j_1,j_2,\ldo ts,j_m)$$-labeli ng of graphs

This paper considers the channel assignment problem in mobile communications systems. Suppose there are many base stations in an area, each of which demands a number of channels to transmit signals. The channels assigned to the same base station must be separated in some extension, and two channels assigned to two different stations that are within a distance must be separated in some other extension according to the distance between the two stations. The aim is to assign channels to stations so that the interference is controlled within an acceptable level and the spectrum of channels used is minimized. This channel assignment problem can be modeled as the multiple t-separated \(L(j_1,j_2,\ldots ,j_m)\)-labeling of the interference graph. In this paper, we consider the case when all base stations demand the same number of channels. This case is referred as n-fold t-separated \(L(j_1,j_2,\ldots ,j_m)\)-labeling of a graph. This paper first investigates the basic properties of n-fold t-separated \(L(j_1,j_2,\ldots ,j_m)\)-labelings of graphs. And then it focuses on the special case when \(m=1\). The optimal n-fold t-separated L(j)-labelings of all complete graphs and almost all cycles are constructed. As a consequence, the optimal n-fold t-separated \(L(j_1,j_2,\ldots ,j_m)\)-labelings of the triangular lattice and the square lattice are obtained for the case \(j_1=j_2=\cdots =j_m\). This provides an optimal solution to the corresponding channel assignment problems with interference graphs being the triangular lattice and the square lattice, in which each base station demands a set of n channels that are t-separated and channels from two different stations at distance at most m must be \(j_1\)-separated. We also study a variation of n-fold t-separated \(L(j_1,j_2,\ldots ,j_m)\)-labeling, namely, n-fold t-separated consecutive \(L(j_1,j_2,\ldots ,j_m)\)-labeling. And present the optimal n-fold t-separated consecutive L(j)-labelings of all complete graphs and cycles.     

Polynomial time approximation scheme for t-latency bounded information propagation problem in?wireless?networks

Latency of information propagating in wireless network is gaining more and more attention recently. This paper studies the problem of t-Latency Bounded Information Propagation (t-LBIP) problem in wireless networks which are represented by unit-disk graphs. So far, no guaranteed approximation algorithm has been achieved for t-LBIP when t≥2. In this paper, we propose a Polynomial Time Approximation Scheme for t-LBIP under the condition that the maximum degree is bounded by a constant.     

Analysis of Two‐Level Support Systems with Time‐Dependent Overflow—A Banking Application

In this paper, we analyze the performance of call centers of financial service providers with two levels of support and a time‐dependent overflow mechanism. Waiting calls from the front‐office queue flow over to the back office if a waiting‐time limit is reached and at least one back‐office agent is available. The analysis of such a system with time‐dependent overflow is reduced to the analysis of a continuous‐time Markov chain with state‐dependent overflow probabilities. To approximate the system with time‐dependent overflow, some waiting‐based performance measures are modified. Numerical results demonstrate the reliability of this Markovian performance approximation for different parameter settings. A sensitivity analysis shows the impact of the waiting‐time limit and the dependence of the performance measures on the arrival rate.     

The planet heals itself: The overkill of Homo sapiens in contemporary literature

Both in the perception of the academia and in the eyes of the public, the overflow of human civilisation on the Earth is considered potentially pernicious, not only for the planet but also for humanity itself. Literature has recently addressed the issue of threats posed by the overabundance and overindulgence of human population. Speculative dystopian fiction is perhaps the most appropriate genre to undertake the discussion of this topic. This paper analyses four selected contemporary dystopian novels by critically acclaimed writers, which develop the theme of the overflow of human civilisation and examine the menaces that it causes on several levels. The works analysed are as follows: Oryx and Crake by Margaret Atwood (2003), Cloud Atlas by David Mitchell (2004), The Road by Cormac McCarthy (2006) and Stone Gods by Jeanette Winterson (2007). Each of the novels presents some form of a post-apocalyptic framework and can therefore be located within the context of ‘overflow’ of human race, which destroys its natural habitat and undermines its own civilisational advances. As I argue, the eradication of the human race is part of the self-purification process undertaken by the planet. By using different literary devices, the four writers suggest that although history repeats itself in circles, human beings are incapable of learning from past mistakes. In the article, I refer to Lovelock's metaphorical use of the concept of Gaia to discuss the ethical and political function of the dystopian literature.     

Supply chain management in the US and Taiwan: An empirical study

This study uses an empirical survey of middle-line managers in the US and Taiwan to study the association of supply chain management components and organizational performance. Through structural equation modeling, critical components of supply chain management are found to have considerable effects on organizational performance. The findings of the study are summarized as follows:

•$•$

Supply chain competencies have positive effects on organizational performance in both the US and Taiwan. Supply chain competencies are developed around quality and service, operations and distribution, and design effectiveness. The goal of supply chain competencies is to satisfy customer requirements.     

Multiperson Bargaining and Strategic Complexity

We investigate the effect of introducing costs of complexity in the n‐person unanimity bargaining game. As is well‐known, in this game every individually rational allocation is sustainable as a Nash equilibrium (also as a subgame perfect equilibrium if players are sufficiently patient and if n & 2). Moreover, delays in agreement are also possible in such equilibria. By limiting ourselves to a plausible notion of complexity that captures length of memory, we find that the introduction of complexity costs (lexicographically with the standard payoffs) does not reduce the range of possible allocations but does limit the amount of delay that can occur in any agreement. In particular, we show that in any n‐player game, for any allocation z, an agreement on z at any period t can be sustained as a Nash equilibrium of the game with complexity costs if and only if t≤n. We use the limit on delay result to establish that, in equilibrium, the strategies implement stationary behavior. Finally, we also show that ‘noisy Nash equilibrium’ with complexity costs sustains only the unique stationary subgame perfect equilibrium allocation.