A Stocking CUM Pricing Model under the Effect of Consumer Behaviour

2003 ◽  
Vol 54 (1-2) ◽  
pp. 71-80
Author(s):  
Suddha Sankar Dutta ◽  
Manisha Pal
Keyword(s):  
Consumer Behaviour ◽  
Risk Model ◽  
Past Experience ◽  
The Other ◽  
Selling Price ◽  
Pricing Model ◽  
Dynamic Risk ◽  
Unmet Demand ◽  
Procurement Cost ◽  
Optimal Values

The paper considers a dynamic risk model with periods of equal length for stocking and selling products where the selling price of the stocked item is under control of the management. A preset price ( y) may appear unsatisfactory to a fraction (1- ψ( y)) of the arrived demand and this fraction of demand is lost irrespective of the stock on hand. The other fraction ( ψ( y)) of the demand is retained if there is stock on hand and in case of stockout a fixed fraction ( π) of the demand, is backlogged whereas (1 - π) of the unmet demand is lost. ψ( y) is decreasing in y. where y is at least as high as the procurement cost, and both ψ( y) and π are either known or can be estimated from past experience. Arrival of demand over a reorder interval is continuous, following some known probabilistic Jaw and is independent of price. Optimal values of stock height and selling price have been obtained through maximization of profit, given that both of them are to be set at the beginning of a reorder interval.

Life Beyond 1MeV

1980 ◽  
Vol 38 ◽  
pp. 30-33
Author(s):  
K.H. Westmacott
Keyword(s):  
Electron Microscopy ◽  
Past Experience ◽  
The Other ◽  
Good Case ◽  
Other Hand ◽  
The U.S

Life beyond 1MeV – like life after 40 – is not too different unless one takes advantage of past experience and is receptive to new opportunities. At first glance, the returns on performing electron microscopy at voltages greater than 1MeV diminish rather rapidly as the curves which describe the well-known advantages of HVEM often tend towards saturation. However, in a country with a significant HVEM capability, a good case can be made for investing in instruments with a range of maximum accelerating voltages. In this regard, the 1.5MeV KRATOS HVEM being installed in Berkeley will complement the other 650KeV, 1MeV, and 1.2MeV instruments currently operating in the U.S. One other consideration suggests that 1.5MeV is an optimum voltage machine – Its additional advantages may be purchased for not much more than a 1MeV instrument. On the other hand, the 3MeV HVEM's which seem to be operated at 2MeV maximum, are much more expensive.

Enhancing the Accuracy of Peak Hourly Demand in Bike-Sharing Systems using a Graph Convolutional Network with Public Transit Usage Data

2021 ◽  
pp. 036119812110120
Author(s):  
Jung-Hoon Cho ◽  
Seung Woo Ham ◽  
Dong-Kyu Kim
Keyword(s):  
Adjacency Matrix ◽  
Public Transit ◽  
Demand Forecasting ◽  
The Other ◽  
Convolutional Network ◽  
Demand Pattern ◽  
Temporal Features ◽  
Unmet Demand ◽  
Bike Sharing ◽  
Main Component

With the growth of the bike-sharing system, the problem of demand forecasting has become important to the bike-sharing system. This study aims to develop a novel prediction model that enhances the accuracy of the peak hourly demand. A spatiotemporal graph convolutional network (STGCN) is constructed to consider both the spatial and temporal features. One of the model’s essential steps is determining the main component of the adjacency matrix and the node feature matrix. To achieve this, 131 days of data from the bike-sharing system in Seoul are used and experiments conducted on the models with various adjacency matrices and node feature matrices, including public transit usage. The results indicate that the STGCN models reflecting the previous demand pattern to the adjacency matrix show outstanding performance in predicting demand compared with the other models. The results also show that the model that includes bus boarding and alighting records is more accurate than the model that contains subway records, inferring that buses have a greater connection to bike-sharing than the subway. The proposed STGCN with public transit data contributes to the alleviation of unmet demand by enhancing the accuracy in predicting peak demand.

scholarly journals Dynamic risk model for Rift Valley fever outbreaks in Kenya based on climate and disease outbreak data

2016 ◽  
Vol 11 (2) ◽  
Author(s):  
David Gikungu ◽  
Jacob Wakhungu ◽  
Donald Siamba ◽  
Edward Neyole ◽  
Richard Muita ◽  
...  
Keyword(s):  
Rift Valley ◽  
Rift Valley Fever ◽  
Risk Model ◽  
Early Warning Systems ◽  
Sub Saharan Africa ◽  
Weather Data ◽  
Brier Score ◽  
Valley Fever ◽  
Dynamic Risk ◽  
Normalised Difference Vegetation Index

Rift Valley fever (RVF) is a mosquito-borne viral zoonotic disease that occurs throughout sub-Saharan Africa, Egypt and the Arabian Peninsula, with heavy impact in affected countries. Outbreaks are episodic and related to climate variability, especially rainfall and flooding. Despite great strides towards better prediction of RVF epidemics, there is still no observed climate data-based warning system with sufficient lead time for appropriate response and mitigation. We present a dynamic risk model based on historical RVF outbreaks and observed meteorological data. The model uses 30-year data on rainfall, temperature, relative humidity, normalised difference vegetation index and sea surface temperature data as predictors. Our research on RVF focused on Garissa, Murang’a and Kwale counties in Kenya using a research design based on a correlational, experimental, and evaluational approach. The weather data were obtained from the Kenya Meteorological Department while the RVF data were acquired from International Livestock Research Institute, and the Department of Veterinary Services. Performance of the model was evaluated by using the first 70% of the data for calibration and the remaining 30% for validation. The assessed components of the model accurately predicted already observed RVF events. The Brier score for each of the models (ranging from 0.007 to 0.022) indicated high skill. The coefficient of determination (R2) was higher in Garissa (0.66) than in Murang’a (0.21) and Kwale (0.16). The discrepancy was attributed to data distribution differences and varying ecosystems. The model outputs should complement existing early warning systems to detect risk factors that predispose for RVF outbreaks.

Nature-Inspired Metaheuristics for Automatic Multilevel Image Thresholding

2014 ◽  
Vol 5 (4) ◽  
pp. 47-69 ◽  
Author(s):  
Salima Ouadfel ◽  
Souham Meshoul
Keyword(s):  
Cuckoo Search ◽  
Exhaustive Search ◽  
The Other ◽  
Multilevel Thresholding ◽  
Bee Colony ◽  
Individual Solution ◽  
Optimal Values ◽  
Comparison Algorithms ◽  
Nature Inspired Metaheuristics ◽  
Better Than

Thresholding is one of the most used methods of image segmentation. It aims to identify the different regions in an image according to a number of thresholds in order to discriminate objects in a scene from background as well to distinguish objects from each other. A great number of thresholding methods have been proposed in the literature; however, most of them require the number of thresholds to be specified in advance. In this paper, three nature-inspired metaheuristics namely Artificial Bee Colony, Cuckoo Search and Bat algorithms have been adapted for the automatic multilevel thresholding (AMT) problem. The goal is to determine the correct number of thresholds as well as their optimal values. For this purpose, the article adopts—for each metaheuristic—a new hybrid coding scheme such that each individual solution is represented by two parts: a real part which represents the thresholds values and a binary part which indicates if a given threshold will be used or not during the thresholding process. Experiments have been conducted on six real test images and the results have been compared with two automatic multilevel thresholding based PSO methods and the exhaustive search method for fair comparison. Empirical results reveal that AMT-HABC and AMT-HCS algorithms performed equally to the solution provided by the exhaustive search and are better than the other comparison algorithms. In addition, the results indicate that the ATM-HABC algorithm has a higher success rate and a speed convergence than the other metaheuristics.

scholarly journals A Competitive Memory Paradigm for Multimodal Optimization Driven by Clustering and Chaos

Mathematics ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 934
Author(s):  
Jorge Gálvez ◽  
Erik Cuevas ◽  
Krishna Gopal Dhal
Keyword(s):  
Optimization Problems ◽  
Optimization Methods ◽  
Global Optimum ◽  
Point Of View ◽  
The Other ◽  
Memory Mechanism ◽  
Dominant Individual ◽  
Complex Optimization ◽  
Optimal Values ◽  
Evolutionary Operators

Evolutionary Computation Methods (ECMs) are proposed as stochastic search methods to solve complex optimization problems where classical optimization methods are not suitable. Most of the proposed ECMs aim to find the global optimum for a given function. However, from a practical point of view, in engineering, finding the global optimum may not always be useful, since it may represent solutions that are not physically, mechanically or even structurally realizable. Commonly, the evolutionary operators of ECMs are not designed to efficiently register multiple optima by executing them a single run. Under such circumstances, there is a need to incorporate certain mechanisms to allow ECMs to maintain and register multiple optima at each generation executed in a single run. On the other hand, the concept of dominance found in animal behavior indicates the level of social interaction among two animals in terms of aggressiveness. Such aggressiveness keeps two or more individuals as distant as possible from one another, where the most dominant individual prevails as the other withdraws. In this paper, the concept of dominance is computationally abstracted in terms of a data structure called “competitive memory” to incorporate multimodal capabilities into the evolutionary operators of the recently proposed Cluster-Chaotic-Optimization (CCO). Under CCO, the competitive memory is implemented as a memory mechanism to efficiently register and maintain all possible optimal values within a single execution of the algorithm. The performance of the proposed method is numerically compared against several multimodal schemes over a set of benchmark functions. The experimental study suggests that the proposed approach outperforms its competitors in terms of robustness, quality, and precision.

scholarly journals Behaviour and decision making of Czech consumers when buying beverages 

2012 ◽  
Vol 52 (No. 7) ◽  
pp. 341-346
Author(s):  
M. Foret ◽  
P. Procházka
Keyword(s):  
Decision Making ◽  
Life Style ◽  
Consumer Behaviour ◽  
Mineral Water ◽  
Secondary Analysis ◽  
Marketing Research ◽  
The Other ◽  
Research Project ◽  
The One ◽  
Consumption Habits

The article deals with the problem of analysis of the factors that influence the behaviour and decision-making of consumers when buying beverages. The analysis was based on data about consumer behaviour obtained within the period of 1993–2004. The secondary analysis involved data collected within the framework of a marketing research project SHOPPING MONITOR performed by the marketing agencies INCOMA Research and GfK Prague in years 1999–2002. Based on the results obtained, it was concluded that hypermarkets were dominating not only as a place of purchasing foodstuffs in general but also as a leading outlet for sale of beverages. Czech consumers preferred Czech brands of beverages and there was a new trend in increasing purchases of tea, juices and mineral water on the one hand and coffee and wine on the other. This indicates a change in consumption habits and reflects an interest in a healthier life style. 

scholarly journals Efficiency of caries risk assessment in young adults using Cariogram

2012 ◽  
Vol 06 (03) ◽  
pp. 270-279 ◽  
Author(s):  
Esra Uzer Celik ◽  
Necmi Gokay ◽  
Mustafa Ates
Keyword(s):  
Risk Assessment ◽  
Young Adults ◽  
Risk Model ◽  
Secretion Rate ◽  
The Other ◽  
Caries Risk ◽  
Caries Risk Assessment ◽  
Risk Models ◽  
Caries Increment ◽  
Caries Progression

ABSTRACTObjectives: The aims of this study were to: (1) evaluate the caries risk in young adults using Cariogram and (2) compare the efficiency of Cariogram with the regression risk models created using the same variables in Cariogram by examining the actual caries progression over a 2-year period.Methods: The aims of this study were to: (1) evaluate the caries risk in young adults using Cariogram and (2) compare the efficiency of Cariogram with the regression risk models created using the same variables in Cariogram by examining the actual caries progression over a 2-year period.Results: Diet frequency, plaque amount and secretion rate were significantly associated with caries increment (P<.05). Cariogram and the regression risk models explained the caries formation at a higher rate than single-variables. However, the regression risk model developed by diet frequency, plaque amount and secretion rate explained the caries formation similar to Cariogram, while the other regression model developed by all variables used in Cariogram explained the caries formation at a higher rate than this computer program.Conclusions: Cariogram is effective and can be used for caries risk assessment instead of single variables; however, it is possible to deve

Positioning selves, doing relational work and constructing identities in interview talk

2013 ◽  
Vol 9 (1) ◽  
Author(s):  
Elizabeth R. Miller
Keyword(s):  
Identity Construction ◽  
Past Experience ◽  
Positioning Theory ◽  
The Other ◽  
Analytic Approach ◽  
Local Interactions ◽  
Self And Other ◽  
Vietnamese Woman ◽  
Relational Work ◽  
Interview Conversation

AbstractThis article draws on positioning theory and uses Bamberg’s (2005) three-level analytic approach to analyze how identity construction and relational work implicate the other and are co-constitutive processes in local interactions. To that end, it examines a sequence of excerpts taken from an interview involving the author and a Vietnamese woman and analyzes the co-constructed positioning of self and other that developed over the course of the interview conversation. The article focuses on how (non)delicate topics are introduced, responded to, modified and developed as the interviewee reports on past experience and adopts evaluative stances toward topics initiated by the interviewer. The study further highlights how normative ideologies are indexed and reconstituted in such talk, and points to their role in making particular identities relevant and in mobilizing relational work in local interactions.

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