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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/3

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Department: search.filters.department.Department of Business AdministrationSubject: search.filters.subject.Mathematics

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Now showing 1 - 5 of 5
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    Optimization applications in scheduling theory - introduction and an overview
    (Springer, 1996) Kouvelis, P.; Department of Business Administration; Karabatı, Selçuk; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 38819
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    A new gravity model with variable distance decay
    (Vilnius Gediminas Technical Univ Press, Technika, 2008) N/A; Department of Business Administration; Department of Business Administration; Sandıkçıoğlu, Müge; Ali, Özden Gür; Sayın, Serpil; Master Student; Faculty Member; Faculty Member; Department of Business Administration; Graduate School of Sciences and Engineering; College of Administrative Sciences and Economics; College of Administrative Sciences and Economics; N/A; 57780; 6755
    Our main goal is to understand the customers' store choice behavior in a grocery retail setting. We see this as a first vital step in order to make store location, format and product promotion decisions in the retail organization Proposed models in the literature generate consumer utility functions for different stores which are used in store sales estimation. For example, in one of its basic forms, Huff model proposes that, utility of a store for an individual is equal to the sales area of the store divided by a power of the individual's distance to the store. Parallel to this stream of research Multiplicative Competitor Interaction model estimates log-transformed utility functions by ordinary least squares regression. It is less specific in terms of variable selection compared to the Huff model. This paper proposes a new market share model which is a variant of the Huff model and evaluates most established market share models such as Huff and Multiplicative Competitor Interaction Model as well as a data mining method in a one-brand heterogonous size retail store setting. We observe that the Huff model performs well in its basic form. By representing distance decay value as a function of the sales area of the retail store we are able to improve the performance of the Huff model. We propose using optimization for estimating the model parameters in certain cases and observe that this improves the generalization ability of the model.
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    Clustering grocery shopping paths of customers by using optimization-based models
    (Vilnius Gediminas Technical Univ Press, Technika, 2008) N/A; Department of Business Administration; Department of Industrial Engineering; Yaman, Tuğba; Karabatı, Selçuk; Karaesmen, Fikri; Master Student; Faculty Member; Faculty Member; Department of Business Administration; Department of Industrial Engineering; Graduate School of Sciences and Engineering; College of Administrative Sciences and Economics; College of Engineering; N/A; 38819; 3579
    This study presents a preliminary investigation of shopping behavior of customers in a grocery store. Using each customer's in-store shopping path information, gathered by a wireless video camera that is affixed to the shopping cart, we classify customers into a predetermined number of clusters, and create a shopping path-based segmentation of customers. For this purpose a number of optimization models are developed. The results are presented in this paper. The next step is to analyze this collected data from different perspectives and developing different optimization models to achieve a better solution to the above clustering problem.
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    Modeling and analysis of output variability in discrete material flow production systems
    (Springer, 2013) Smit, J. MacGregor; Department of Business Administration; Tan, Barış; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 28600
    Developing analytical models for performance evaluation of production systems has been subject to numerous studies in the literature [4, 15, 24]. The main focus in most of these studies has been on utilizing Markovian models and deriving various first-order performance measures from the steady-state probabilities. The most commonly used performance measure in these studies is the throughput that is defined as the number of products produced per unit time in the long run. In addition average inventory levels, the average time spent in the system, probability of stock-out, probability of blocking and starvation are also used to design and control production systems by using these analytical models.
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    Computing the nadir point for multiobjective discrete optimization problems
    (Springer, 2015) N/A; N/A; Department of Business Administration; Kirlik, Gökhan; Sayın, Serpil; PhD Student; Faculty Member; Department of Business Administration; Graduate School of Sciences and Engineering; College of Administrative Sciences and Economics; N/A; 6755
    We investigate the problem of finding the nadir point for multiobjective discrete optimization problems (MODO). The nadir point is constructed from the worst objective values over the efficient set of a multiobjective optimization problem. We present a new algorithm to compute nadir values for MODO with objective functions. The proposed algorithm is based on an exhaustive search of the -dimensional space for each component of the nadir point. We compare our algorithm with two earlier studies from the literature. We give numerical results for all algorithms on multiobjective knapsack, assignment and integer linear programming problems. Our algorithm is able to obtain the nadir point for relatively large problem instances with up to five-objectives.