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Department: search.filters.department.Department of Industrial EngineeringSubject: search.filters.subject.Mathematics

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Now showing 1 - 10 of 23
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    A constant-factor approximation algorithm for multi-vehicle collection for processing problem
    (Springer Heidelberg, 2013) Gel, Esma S.; N/A; Department of Industrial Engineering; Department of Industrial Engineering; Department of Industrial Engineering; Yücel, Eda; Salman, Fatma Sibel; Örmeci, Lerzan; PhD Student; Faculty Member; Faculty Member; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; 235501; 178838; 32863
    We define the multiple-vehicle collection for processing problem (mCfPP) as a vehicle routing and scheduling problem in which items that accumulate at customer sites over time should be transferred by a series of tours to a processing facility. We show that this problem with the makespan objective (mCfPP()) is NP-hard using an approximation preserving reduction from a two-stage, hybrid flowshop scheduling problem. We develop a polynomial-time, constant-factor approximation algorithm to solve mCfPP(). The problem with a single site is analyzed as a special case with two purposes. First, we identify the minimum number of vehicles required to achieve a lower bound on the makespan, and second, we characterize the optimal makespan when a single vehicle is utilized.
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    Bayesian analysis of Markov modulated Bernoulli processes
    (Springer, 2003) Soyer, R.; Department of Industrial Engineering; Department of Industrial Engineering; Özekici, Süleyman; Faculty Member; College of Engineering; 32631
    We consider Markov Modulated Bernoulli Processes (MMBP) where the success probability of a Bernoulli process evolves over time according to a Markov chain. The MMBP is applied in reliability modeling where systems and components function in a randomly changing environment. Some of these applications include, but are not limited to, reliability assessment in power systems that are subject to fluctuating weather conditions over time and reliability growth processes that are subject to design changes over time. We develop a general setup for analysis of MMBPs with a focus on reliability modeling and present Bayesian analysis of failure data and illustrate how reliability predictions can be obtained.
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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; Department of Business Administration; Department of Industrial Engineering; Yaman, Tuğba; Karabatı, Selçuk; Karaesmen, Fikri; Master Student; Faculty Member; Faculty Member; 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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    Competitive analysis of randomized online strategies for the multi-agent k-Canadian traveler problem
    (Springer, 2019) N/A; Department of Industrial Engineering; Department of Industrial Engineering; Shiri, Davood; Salman, Fatma Sibel; PhD Student; Faculty Member; Graduate School of Sciences and Engineering; College of Engineering; N/A; 178838
    In this article, we study randomized online strategies for the multi-agent k-Canadian Traveler Problem which is defined on an undirected graph with a given source node O and a destination node D. Non-negative edge costs are given. The traveling agents are initially at O. There are k blocked edges in the graph, but these edges are not known to the agents. A blocked edge is learned when at least one of the agents arrives at one of its end-nodes. The objective is to find an online strategy such that at least one of the agents finds a route from O to D with minimum travel cost. We analyze the problem in three cases: (1) without communication, (2) with limited communication, and (3) with complete communication. We derive lower bounds on the competitive ratio of randomized online strategies for these cases. We show that increasing the number of agents can improve the competitive ratio of randomized online strategies when there is no communication between agents. We introduce a randomized online strategy which is optimal for both cases with limited and complete communication on O-D edge-disjoint graphs. We also prove that the competitive ratio of the optimal randomized strategy does not improve on O-D edge-disjoint graphs, when the case with complete communication is compared to the case with limited communication.
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    PublicationOpen Access
    GoNDEF: an exact method to generate all non-dominated points of multi-objective mixed-integer linear programs
    (Springer, 2019) Department of Industrial Engineering; N/A; Department of Industrial Engineering; Türkay, Metin; Rasmi, Seyyed Amir Babak; Faculty Member; PhD Student; College of Engineering; Graduate School of Sciences and Engineering; 24956; N/A
    Most real-world problems involve multiple conflicting criteria. These problems are called multi-criteria/multi-objective optimization problems (MOOP). The main task in solving MOOPs is to find the non-dominated (ND) points in the objective space or efficient solutions in the decision space. A ND point is a point in the objective space with objective function values that cannot be improved without worsening another objective function. In this paper, we present a new method that generates the set of ND points for a multi-objective mixed-integer linear program (MOMILP). The Generator of ND and Efficient Frontier (GoNDEF) for MOMILPs finds that the ND points represented as points, line segments, and facets consist of every type of ND point. First, the GoNDEF sets integer variables to the values that result in ND points. Fixing integer variables to specific values results in a multi-objective linear program (MOLP). This MOLP has its own set of ND points. A subset of this set establishes a subset of the ND points set of the MOMILP. In this paper, we present an extensive theoretical analysis of the GoNDEF and illustrate its effectiveness on a set of instance problems.
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    Modeling and simulation of metabolic networks for estimation of biomass accumulation parameters
    (Elsevier, 2009) Biegler, L.; Karasozen, Bülent; N/A; Department of Industrial Engineering; Department of Industrial Engineering; Kaplan, Uğur; Türkay, Metin; PhD Student; Faculty Member; Graduate School of Sciences and Engineering; College of Engineering; N/A; 24956
    Metabolic networks are defined as the collection of biochemical reactions within a cell that define the functions of that cell. Due to the growing need to understand the functions of biological organisms for industrial and medical purposes, modeling and simulation of metabolic networks has attracted a lot of attention recently. Traditionally, metabolic networks are modeled such as flux-balance analysis that considers the steady state nature of the cell. However, it is important to consider the dynamic behavior of a cell since the environmental conditions change continuously. Sometimes due to the critical changes in the environment some of the reactions exhibit completely different behavior leading to discrete changes in the metabolic network. Therefore, a cell exhibits discrete-continuous behavior in continuous time. Since hybrid systems exhibit the same characteristics modeling a cell as a hybrid system gives an accurate representation. The aim of this paper is to develop a simulation framework to model the evolving structure of the cell metabolism under changes in the environment. The metabolic responses that cell gives, against multiple changes in the environment are not fully understood. Therefore, in this study, a cell is modeled as a hybrid system that is composed of a system of differential and algebraic equations. The changes in the concentration of metabolites in the environment are represented by Ordinary Differential Equations and the intracellular cell metabolism is represented by a set of algebraic equations. TO understand the feedback relationship between intracellular and extracellular changes, the system is solved considering the effects of extracellular stresses on the metabolic responses. (c) 2008 Elsevier B.V. .
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    Modeling earthquake vulnerability of highway networks
    (Elsevier, 2013) N/A; Department of Industrial Engineering; Department of Industrial Engineering; Arşık, İdil; Salman, Fatma Sibel; Master Student; Faculty Member; Graduate School of Sciences and Engineering; College of Engineering; N/A; 178838
    In this study, we investigate the earthquake vulnerability of highway networks whose links are subject to failure. We propose a model called α- conservative failure model that aims to capture the dependency among link failures in the event of an earthquake. According to this model, we calculate a path-based accessibility measure to assess the expected weighted average shortest distance to serve a unit demand after the earthquake. We test the proposed link failure model on a case study of the earthquake vulnerability in Istanbul.
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    Multiple facility location on a network with linear reliability order of edges
    (Springer, Van Godewijckstraat, 2017) Hassin, Refael; Ravi, R.; Department of Industrial Engineering; Department of Industrial Engineering; Salman, Fatma Sibel; Faculty Member; College of Engineering; 178838
    We study the problem of locating facilities on the nodes of a network to maximize the expected demand serviced. The edges of the input graph are subject to random failure due to a disruptive event. We consider a special type of failure correlation. The edge dependency model assumes that the failure of a more reliable edge implies the failure of all less reliable ones. Under this dependency model called Linear Reliability Order (LRO) we give two polynomial time exact algorithms. When two distinct LRO's exist, we prove the total unimodularity of a linear programming formulation. In addition, we show that minimizing the sum of facility opening costs and expected cost of unserviced demand under two orderings reduces to a matching problem. We prove NP-hardness of the three orderings case and show that the problem with an arbitrary number of orderings generalizes the deterministic maximum coverage problem. When a demand point can be covered only if a facility exists within a distance limit, we show that the problem is NP-hard even for a single ordering.
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    Newsvendor models with dependent random supply and demand
    (Springer Heidelberg, 2014) N/A; N/A; Department of Industrial Engineering; Department of Industrial Engineering; Department of Industrial Engineering; Okyay, Hayrettin Kaan; Karaesmen, Fikri; Özekici, Süleyman; Master Student; Faculty Member; Faculty Member; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; N/A; 3579; 32631
    The newsvendor model is perhaps the most widely analyzed model in inventory management. In this single-period model, the only source of randomness is the demand during the period and one tries to determine the optimal order quantity in view of various cost factors. We consider an extention where supply is also random so that the quantity ordered is not necessarily received in full at the beginning of the period. Such models have been well-received in the literature with the assumption of independence between demand and supply. In this setting, we suppose that the random demand and supply are not necessarily independent. We focus on the resulting optimization problem and provide interesting characterizations on the optimal order quantity.
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    On the online multi-agent O-D k-Canadian traveler problem
    (Springer, 2017) N/A; Department of Industrial Engineering; Department of Industrial Engineering; Shiri, Davood; Salman, Fatma Sibel; PhD Student; Faculty Member; Graduate School of Sciences and Engineering; College of Engineering; N/A; 178838
    In this article, we present new results on the online multi-agent O–D k-Canadian Traveler Problem, in which there are multiple agents and an input graph with a given source node O and a destination node D together with edge costs such that at most k edges are blocked. The blocked edges are not known a priori and are not recoverable. All of the agents are initially located at O. The objective is to find an online strategy such that at least one of the agents finds a route from the initial location O to a given destination D with minimum total cost. We focus on the case where communication among the agents is limited in the sense that some travelers can both send and receive information while the others can only receive information. We formalize the definition of agents’ intelligence by specifying three levels. We introduce two online strategies which utilize higher levels of agents’ intelligence to provide updated lower bounds to this problem. We show that one of our strategies is optimal in both cases with complete and limited communication in the special case of O–D edge-disjoint graphs and highest level of agents’ intelligence.