The choice of the model in inventory control and the cost of sophistication

This thesis is concerned with the inventory control of items that can be considered independent of one another. The decisions when to order and in what quantity, are the controllable or independent variables in cost expressions which are minimised. The four systems considered are referred to as (Q, R), (nQ,R,T), (M,T) and (M,R,T). Wiith ((Q,R) a fixed quantity Q is ordered each time the order cover (i.e. stock in hand plus on order ) equals or falls below R, the re-order level. With the other three systems reviews are made only at intervals of T. With (nQ,R,T) an order for nQ is placed if on review the inventory cover is less than or equal to R, where n, which is an integer, is chosen at the time so that the new order cover just exceeds R. In (M, T) each order increases the order cover to M. Fnally in (M, R, T) when on review, order cover does not exceed R, enough is ordered to increase it to M. The (Q, R) system is examined at several levels of complexity, so that the theoretical savings in inventory costs obtained with more exact models could be compared with the increases in computational costs. Since the exact model was preferable for the (Q,R) system only exact models were derived for theoretical systems for the other three. Several methods of optimization were tried, but most were found inappropriate for the exact models because of non-convergence. However one method did work for each of the exact models. Demand is considered continuous, and with one exception, the distribution assumed is the normal distribution truncated so that demand is never less than zero. Shortages are assumed to result in backorders, not lost sales. However, the shortage cost is a function of three items, one of which, the backorder cost, may be either a linear, quadratic or an exponential function of the length of time of a backorder, with or without period of grace. Lead times are assumed constant or gamma distributed. Lastly, the actual supply quantity is allowed to be distributed. All the sets of equations were programmed for a KDF 9 computer and the computed performances of the four inventory control procedures are compared under each assurnption.

Aircraft rotable inventory optimisation: development of a new solution

Analysis of the use of ICT in the aerospace industry has prompted the detailed investigation of an inventory-planning problem. There is a special class of inventory, consisting of expensive repairable spares for use in support of aircraft operations. These items, called rotables, are not well served by conventional theory and systems for inventory management. The context of the problem, the aircraft maintenance industry sector, is described in order to convey some of its special characteristics in the context of operations management. A literature review is carried out to seek existing theory that can be applied to rotable inventory and to identify a potential gap into which newly developed theory could contribute. Current techniques for rotable planning are identified in industry and the literature: these methods are modelled and tested using inventory and operational data obtained in the field. In the expectation that current practice leaves much scope for improvement, several new models are proposed. These are developed and tested on the field data for comparison with current practice. The new models are revised following testing to give improved versions. The best model developed and tested here comprises a linear programming optimisation, which finds an optimal level of inventory for multiple test cases, reflecting changing operating conditions. The new model offers an inventory plan that is up to 40% less expensive than that determined by current practice, while maintaining required performance.

Sensitivity Analysis of Some Applied Probability Models

2000 Mathematics Subject Classi cation: Primary 90C31. Secondary 62C12, 62P05, 93C41.

Examining Technology Adoption and Management Perception of Inventory Management Systems: The Case of Aruba Restaurants

The purpose of this paper is to explore the use of automated inventory management systems (IMS) and identify the stage of technology adoption for restaurants in Aruba. A case study analysis involving twelve members of the Aruba Gastronomic Association was conducted using a qualitative research design to gather information on approaches currently used as well as the reasons and perceptions managers/owners have for using or not using automated systems in their facilities. This is the first study conducted using the Aruba restaurant market. Therefore, the application of two technology adoption models was used to integrate critical factors relevant to the study. Major findings indicated the use of an automated IMS in restaurants is limited, thus underscoring the lack of adoption of technology in this area. The results also indicated that two major reasons that restaurants are not adopting IMS technology are budgetary constraints and service support. This study is imperative for two reasons: (1) the results of this study can be used as a comparison for future IMS adoption, not only for Aruba’s restaurant industry but also for other Caribbean destinations and the U.S., (2) this study also provides insight into the additional training and support help needed in hospitality technology services.

Transferability of Regional Permafrost Disturbance Susceptibility Modelling Using Generalized Linear and Generalized Additive Models

To effectively assess and mitigate risk of permafrost disturbance, disturbance-p rone areas can be predicted through the application of susceptibility models. In this study we developed regional susceptibility models for permafrost disturbances using a field disturbance inventory to test the transferability of the model to a broader region in the Canadian High Arctic. Resulting maps of susceptibility were then used to explore the effect of terrain variables on the occurrence of disturbances within this region. To account for a large range of landscape charac- teristics, the model was calibrated using two locations: Sabine Peninsula, Melville Island, NU, and Fosheim Pen- insula, Ellesmere Island, NU. Spatial patterns of disturbance were predicted with a generalized linear model (GLM) and generalized additive model (GAM), each calibrated using disturbed and randomized undisturbed lo- cations from both locations and GIS-derived terrain predictor variables including slope, potential incoming solar radiation, wetness index, topographic position index, elevation, and distance to water. Each model was validated for the Sabine and Fosheim Peninsulas using independent data sets while the transferability of the model to an independent site was assessed at Cape Bounty, Melville Island, NU. The regional GLM and GAM validated well for both calibration sites (Sabine and Fosheim) with the area under the receiver operating curves (AUROC) N 0.79. Both models were applied directly to Cape Bounty without calibration and validated equally with AUROC's of 0.76; however, each model predicted disturbed and undisturbed samples differently. Addition- ally, the sensitivity of the transferred model was assessed using data sets with different sample sizes. Results in- dicated that models based on larger sample sizes transferred more consistently and captured the variability within the terrain attributes in the respective study areas. Terrain attributes associated with the initiation of dis- turbances were similar regardless of the location. Disturbances commonly occurred on slopes between 4 and 15°, below Holocene marine limit, and in areas with low potential incoming solar radiation

On Queueinginventory Models – product form solution; reservation, Cancellation and common life time

Queueing theory is the mathematical study of ‘queue’ or ‘waiting lines’ where an item from inventory is provided to the customer on completion of service. A typical queueing system consists of a queue and a server. Customers arrive in the system from outside and join the queue in a certain way. The server picks up customers and serves them according to certain service discipline. Customers leave the system immediately after their service is completed. For queueing systems, queue length, waiting time and busy period are of primary interest to applications. The theory permits the derivation and calculation of several performance measures including the average waiting time in the queue or the system, mean queue length, traffic intensity, the expected number waiting or receiving service, mean busy period, distribution of queue length, and the probability of encountering the system in certain states, such as empty, full, having an available server or having to wait a certain time to be served.

School Anxiety Inventory: Reliability and Validity Evidence in a Sample of Slovenian Adolescents

The purpose of this study was to examine the reliability and validity of the School Anxiety Inventory (SAI) using a sample of 646 Slovenian adolescents (48% boys), ranging in age from 12 to 19 years. Single confirmatory factor analyses replicated the correlated four-factor structure of scores on the SAI for anxiety-provoking school situations (Anxiety about School Failure and Punishment, Anxiety about Aggression, Anxiety about Social Evaluation, and Anxiety about Academic Evaluation), and the three-factor structure of the anxiety response systems (Physiological Anxiety, Cognitive Anxiety, and Behavioral Anxiety). Equality of factor structures was compared using multigroup confirmatory factor analyses. Measurement invariance for the four- and three-factor models was obtained across gender and school-level samples. The scores of the instrument showed high internal reliability and adequate test–retest reliability. The concurrent validity of the SAI scores was also examined through its relationship with the Social Anxiety Scale for Adolescents (SASA) scores and the Questionnaire about Interpersonal Difficulties for Adolescents (QIDA) scores. Correlations of the SAI scores with scores on the SASA and the QIDA were of low to moderate effect sizes.

APPLICATION OF AN IMPUTATION METHOD FOR GEOSPATIAL INVENTORY OF FOREST STRUCTURAL ATTRIBUTES ACROSS MULTIPLE SPATIAL SCALES IN THE LAKE STATES, U.S.A.

Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.