Service Package Switching in Hotel Revenue Management Systems

Revenue Management Systems (RMS) are commonly used in the hotel industry to maximize revenues in the short term. The forecasting‐allocation module is a key tactical component of a hotel RMS. Forecasting involves estimating demand for service packages across all stayover nights in a planning horizon. A service package is a unique combination of physical room, amenities, room price, and advance purchase restrictions. Allocation involves parsing the room inventory among these service packages to maximize revenues. Previous research and existing revenue management systems assume the demand for a service package to be independent of which service packages are available for sale. We develop a new forecasting‐allocation approach that explicitly accounts for this dependence. We compare the performance of the new approach against a baseline approach using a realistic hotel RMS simulation. The baseline approach reflects previous research and existing industry practice. The new approach produces an average revenue increase of at least 16% across scenarios that reflect existing industry conditions.     

A Comparative Evaluation of Labor Tour Scheduling Methods

This paper presents an initial study of relative performance for a number of the labor tour scheduling heuristic methods proposed in the literature. These heuristic methods were classified as either linear programming (LP) based or construction. Each of the methods was applied to a tour scheduling problem, subject to a variety of labor demand requirements distributions, with the singular objective being the minimization of total labor hours scheduled. Statistical analysis revealed that effective tour schedule solutions were generated by both LP-based and construction methods. Since the performances of the Keith [13], Morris and Showalter [18], and Bechtold and Showalter [5] methods were superior, their solutions were also compared across a number of secondary criteria. An overall analysis of the performances of these three methods resulted in the identification of a number of important managerial and decision-making issues. We conclude that service operations management should consider integrating these heuristic methods into a decision support system. Finally, suggestions for future research are provided.     

Restaurant Revenue Management at Chevys: Determining the Best Table Mix

Revenue management has been used in a variety of industries and generally takes the form of managing demand by manipulating length of customer usage and price. Supply mix is rarely considered, although it can have considerable impact on revenue. In this research, we focused on developing an optimal supply mix, specifically on determining the supply mix that would maximize revenue. We used data from a Chevys restaurant, part of a large chain of Mexican restaurants, in conjunction with a simulation model to evaluate and enumerate all possible supply (table) mixes. Compared to the restaurant's existing table mix, the optimal mix is capable of handling a 30% increase in customer volume without increasing waiting times beyond their original levels. While our study was in a restaurant context, the results of this research are applicable to other service businesses.     

A Framework for Estimating Benefits of Using Auctions in Revenue Management*

We develop a stochastic model to explore the benefits of incorporating auctions in revenue management. To the best of our knowledge the extant literature on modeling in revenue management has not considered auctions. We consider three models, namely, a traditional fixed price (non‐auction) model, a pure auction model, and a hybrid auction model and evaluate their revenue performance under a variety of conditions. The hybrid approach outperforms the other two in all 24 scenarios and yields an average revenue increase of 16.1% over the next best. A surprise finding is that there is no significant difference between the performance of the fixed price and pure auction approaches. A sensitivity analysis reveals that the relative superiority of the hybrid revenue management strategy is reasonably robust.     

Viability of Auction‐Based Revenue Management in Sequential Markets

The Internet is providing an opportunity to revenue management practitioners to exploit the potential of auctions as a new price distribution channel. We develop a stochastic model for a high‐level abstraction of a revenue management system (RMS) that allows us to understand the potential of incorporating auctions in revenue management in the presence of forecast errors associated with key parameters. Our abstraction is for an environment where two market segments book in sequence and revenue management approaches consider auctions in none, one, or both segments. Key insights from our robust results are (i) limited auctions are best employed closest to the final sale date, (ii) counterbalancing forecast errors associated with overall traffic intensity and the proportion of customer arrivals in a segment is more important if an auction is adopted in that segment, and (iii) it is critically important not to err on the side of overestimating market willingness to pay.     

A COMPARISON OF SEQUENCING RULES FOR A TWO-STATE HYBRID FLOW SHOP

A common manufacturing environment in many industries (such as the glass, steel, paper, costume jewelry, and textile industries) is a hybrid flow shop. This system has continuous-process machinery in the fist state of manufacturing and repetitive-batch equipment in the second. Little research has investigated this type system. Scheduling managers of hybrid flow shops tend either to use existing job-shop rules or to devise their own rules. These approaches often are less than adequate for efficient scheduling. In this paper we extend the rule presented by Narasimhan and Panwalker [4] to include a general class of hybrid flow shops. This extenstion, called the generalized cumulative minimum-deviation (GCMD) rule, is compared under various operation conditions to three other sequencing rules: shortest processing time, longest processing time, and minimum deviation. The operating conditions are determined by the number of machines at both stages. The results of 7200 simulation runs demonstrate that the GCMD rule is better than the other rules in minimizing each of five chosen criteria. Thus, the GCMD rule can help managers to schedule hybrid flow shops efficiently to achieve various corporate objectives.     

DYNAMIC LOT SIZING FOR A SINGLE-FACILITY MULTIPRODUCT PROBLEM IN A ROLLING-HORIZON ENVIRONMENT

This paper considers a production planning model for a single-facility multiproduct problem where backlogging is not allowed. A planning-horizon theorem is derived. From that theorem, a forward algorithm for finding an optimal solution over a finite horizon and a procedure for selecting the first-period production in a rolling-horizon environment are developed. Computational results from a set of simulation experiments designed to investigate the cost effectiveness of the procedure demonstrate its effectiveness.     

Tour Scheduling and Task Assignment of a Heterogeneous Work Force: A Heuristic Approach

The 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.     

IMPLICIT OPTIMAL AND HEURISTIC LABOR STAFFING IN A MULTIOBJECTIVE,MULTILOCATION ENVIRONMENT*

This 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.     

Management Policies to Improve the Effectiveness of Multi-Station Service Organizations*

A SLAM based simulation model of a multi-station, tandem queuing structure characteristic of a variety of service systems is employed to test various design options for the system. The model is based on an extensive study of the State of Florida driver licensing offices. The multiple objectives of low time in the system for customers and the efficient use of personnel resources are employed to measure the benefits of policy options. The use of simulation analysis permits the incorporation of complex system characteristics, therefore providing a realistic representation of the effects of possible management actions. Effective methods to control labor in such systems are suggested.     

Efficient Heuristics for MRP Lot Sizing with Variable Production/Purchasing Costs*

Two heuristics based on branch and bound (B&B) are developed to solve closed-loop material requirements planning (MRP) lot-sizing problems that have general product structures and variable costs. A “look ahead method'’(LAM) heuristic allows for variable production/purchasing costs and uses a single-level B&B procedure to rapidly improve lower bound values; thus, LAM efficiently uses computer-storage capacity and allows solution of larger problems. The “total average modification'’(TAM) heuristic uses B&B, applied level by level, and modified setup and carrying costs to solve the variable production/purchasing costs MRP lot-sizing problem. LAM and TAM are tested on problems and compared to heuristics in the literature. TAM may be used to solve large MRP lot-sizing problems encountered in practice.     

Equivalent Alternate Solutions for the Tour Scheduling Problem*

Achieving minimum staffing costs, maximum employee satisfaction with their assigned schedules, and acceptable levels of service are important but potentially conflicting objectives when scheduling service employees. Existing employee scheduling models, such as tour scheduling or general employee scheduling, address at most two of these criteria. This paper describes a heuristic to improve tour scheduling solutions provided by other procedures, and generate a set of equivalent cost feasible alternatives. These alternatives allow managers to identify solutions with attractive secondary characteristics, such as overall employee satisfaction with their assigned tours or consistent employee workloads and customer response times. Tests with both full-time and mixed work force problems reveal the method improves most nonoptimal initial heuristic solutions. Many of the alternatives generated had more even distributions of surplus staff than the initial solutions, yielding more consistent customer response times and employee workloads. The likelihood of satisfying employee scheduling preferences may also be increased since each alternative provides a different deployment of employees among the available schedules.     

Dynamic Group Scheduling Heuristics in a Flow-through Cell Environment*

The increased use of cellular manufacturing configurations designed to grapple with increasing competitive pressures is providing manufacturing managers and engineers with a broad variety of operational challenges. Many questions concerning the best procedures and policies for the day-to-day operation of manufacturing cells are still unanswered. The primary objective of this study is to compare the performance of traditional single-stage heuristics and the two-stage group scheduling heuristics that have exhibited superior performance in previous studies in a flow-through cell environment under a rigorous set of experimental conditions. Such a comparison is of great interest since each previous study has focused on proposing new heuristics and testing them against some particular baseline heuristic, often without comprehensive comparisons to the broad variety of previously proposed heuristics. Two single-stage heuristics and four two-stage heuristics are examined under sixteen experimental conditions (four experimental factors at two levels each). The experimental factors examined are shop load, due date tightness, setup to run-time ratio, and interarrival time distribution. Results vary by experimental condition and performance criteria, but in general, two-stage heuristics outperformed single-stage heuristics under all experimental conditions, as well as being relatively insensitive to changing experimental conditions. In addition, two of the two-stage heuristics displayed superior performance on all performance measures under most experimental conditions. Finally, the results indicated that interarrival time distribution does have a major impact on the performance of scheduling heuristics.     

Scheduling to Improve Field Service Quality*

This research addresses the problem of scheduling technicians to travel from customer site to customer site to perform emergency maintenance on office machines, computers, robots, telecommunications equipment, medical equipment, heating/cooling equipment, household appliances, and other equipment. We call this the Traveling Technician Problem (TTP). In its simplest form, the TTP is a multiserver, sequence-dependent, tardiness minimization problem. This research frames the TTP as a service quality maximization problem in which service quality is defined in terms of mean tardiness, mean technician phone response time, mean promise time, and mean response time. Tardiness is defined with respect to contractually guaranteed response times. Industry practice is to use dispatching rules to assign service calls to technicians. This research proposes scheduling procedures to maximize field service quality in a dynamic environment. A simulation experiment was used to compare three dispatching rules and three scheduling procedures for the TTP. The scheduling procedures dominated the dispatching rules on all four service quality measures. The proposed scheduling procedures hold promise for improving service quality in a wide variety of field service organizations and in other scheduling environments as well.     

Optimizing Service Attributes: The Seller's Utility Problem*

Service designers predict market share and sales for their new designs by estimating consumer utilities. The service's technical features (for example, overnight parcel delivery), its price, and the nature of consumer interactions with the service delivery system influence those utilities. Price and the service's technical features are usually quite objective and readily ascertained by the consumer. However, consumer perceptions about their interactions with the service delivery system are usually far more subjective. Furthermore, service designers can only hope to influence those perceptions indirectly through their decisions about nonlinear processes such as employee recruiting, training, and scheduling policies. Like the service's technical features, these process choices affect quality perceptions, market share, revenues, costs, and profits. We propose a heuristic for the NP‐hard service design problem that integrates realistic service delivery cost models with conjoint analysis. The resulting seller's utility function links expected profits to the intensity of a service's influential attributes and also reveals an ideal setting or level for each service attribute. In tests with simulated service design problems, our proposed configurations compare quite favorably with the designs suggested by other normative service design heuristics.     

An Experimental Comparison of Dispatching Rules for Field Service Support*

Field service repair management is increasing in importance as “high tech” machines such as computers, communication systems, and copy machines are becoming more popular and more widely disbursed geographically. Complicating the management of these systems are response time performance guarantees (e.g., 8-hour response time), which are a popular marketing tool for many field service businesses [21]. These response time), guarantees especially complicate the field service dispatching problem. With response time guarantees, dispatchers must consider travel times and other issues to determine which call should be assigned to an available technician. This research proposes several dispatching rules that might be applied for dispatching sequential-trip technicians in this environment and compares these rules in a simulation experiment to determine which rule is best in terms of average tardiness. The proposed composite travel time-expiration time rule was found to be the best on average tardiness performance and on all other tardiness-related measures. Given the increased importance of tardiness performance in field service organizations, the proposed composite rule appears to have promise.     

Improving Revenue Management Decision Making for Airlines by Evaluating Analyst‐Adjusted Passenger Demand Forecasts*

To maximize revenue, airline revenue management analysts (RMAs) attempt to protect the right number of seats for late‐booking, high‐revenue‐generating passengers from low‐valued leisure passengers. Simulation results in the past showed that a major airline can generate approximately $500 million per year through efficient RM operations. Accurate passenger demand forecasts are required, because reduced forecast error significantly improves revenue. RMAs often adjust the system forecasts to improve revenue opportunity. Analysis of system forecast performance and analyst adjustment is complex, because one must account for all unseen demands throughout the life of a flight. This article proposes a method to account for unseen demand and evaluate forecast performance (adjusted or unadjusted) through a forecast monitoring system. Initial results from one major airline's origin‐destination market data justify the value of RMA forecasting adjustments.     

Tandem Configuration Automated Guided Vehicle Systems: A Comparative Study*

Automated guided vehicle (AGV) systems provide the flexibility and integration required for flexible manufacturing systems. Previous AGV system studies have attempted to reduce the controlling complexities commonly encountered in these systems. However, this has not been accomplished without additional resources (e.g., automated guided vehicles) and lower system flexibility. The primary objective of this study is to compare the performance of AGV system configurations that reduce controlling and modification complexities (i.e., tandem configurations) to traditional AGV system configuration. Three AGV system configurations were tested under 16 experimental conditions. Performance metrics considered were AGV utilization, mean flowtime, mean tardiness, and percent tardy. The results of this study extend the findings of the previous studies in demonstrating the viability of tandem configurations, in that the tandem configurations match the performance of traditional configuration across all performance metrics, without sacrificing ease of control and system flexibility. Finally, the cost tradeoffs inherent in selecting a particular configuration are discussed.     

A DISCRETE PRODUCTION SWITCHING RULE FOR AGGREGATE PLANNING

Aggregate planning (AP) is a necessary activity for manufacturing and services alike. A shift toward high-volume batch and continuous flow processes within American manufacturing has given rise to increasing numbers of crew-loaded facilities. A majority of AP approaches incorporate continuous decision variables and require frequent adjustments to both production and work-force settings. Despite the availability and diversity of these approaches, few significant applications have been reported. This paper presents the detailed development of a discrete AP switching rule that can be applied to a variety of cost environments. Inventory costs are estimated using an interval approach rather than traditional point estimates. The model allows incorporation of overtime options and is interactive in nature. Decision variables from the model can be disaggregated and linked directly to lower-level planning activities. Actual results of model implementation are reported. An overview of the model's incorporation into the larger context of hierarchical production planning is found in [21].     

Improving the Utilization of Front-Line Service Delivery System Personnel*

There are two types of work typically performed in services which differ in the degree of control management has over when the work must be done. Serving customers, an activity that can occur only when customers are in the system is, by its nature, uncontrollable work. In contrast, the execution of controllable work does not require the presence of customers, and is work over which management has some degree of temporal control. This paper presents two integer programming models for optimally scheduling controllable work simultaneously with shifts. One model explicitly defines variables for the times at which controllable work may be started, while the other uses implicit modeling to reduce the number of variables. In an initial experiment of 864 test problems, the latter model yielded optimal solutions in approximately 81 percent of the time required by the former model. To evaluate the impact on customer service of having front-line employees perform controllable work, a second experiment was conducted simulating 5, 832 service delivery systems. The results show that controllable work offers a useful means of improving labor utilization. Perhaps more important, it was found that having front-line employees perform controllable work did not degrade the desired level of customer service.