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Item A Hybrid Simulated Annealing For A Multi-Objective Stochastic Assembly Line Balancing Problem(2008) Cakir, Burcin; Dengiz, Berna; Altiparmak, Fulya; Xia, GP; Deng, XQ; 0000-0003-1730-4214; AAF-7020-2021Asssembly line balancing is the problem of assigning tasks to the workstations, while optimizing one or more objectives without violating restrictions imposed on the line. In practice, task times may be random due to the worker fatigue, low skill levels, job dissatisfaction, poorly maintained equipment, defects in raw material, etc. When stochastic task times are taken consideration in assembly lines, balancing procedure is more complex due to the probability of incompleteness of stations times in a given cycle time. In this study, a multi-objective simulated annealing algorithm (m_SAA) is proposed for single-model, stochastic assembly line balancing problem with the aim of minimizing of smoothness index and total design cost. To obtain Pareto-optimal solutions, m_SAA implements tabu list and a multinomial probability mass function approach. The effectiveness of the proposed m_SAA is comparatively investigated using another SA using weight-sum approach on the test problems. Computational results show that m_SAA with multinomial probability mass function approach is more effective than SA with weight-sum approach in terms of quality of Pareto-optimal solutions.Item A General Neural Network Model for Estimating Telecommunications Network Reliability(2009) Altiparmak, Fulya; Dengiz, Berna; Smith, Alice E.; 0000-0003-1730-4214; 0000-0001-8808-0663; AAF-7020-2021; AAK-2318-2021This paper puts forth a new encoding method for using neural network models to estimate the reliability of telecommunications networks with identical link reliabilities. Neural estimation is computationally speedy, and can be used during network design optimization by an iterative algorithm such as tabu search, or simulated annealing. Two significant drawbacks of previous approaches to using neural networks to model system reliability are the long vector length of the inputs required to represent the network link architecture, and the specificity of the neural network model to a certain system size. Our encoding method overcomes both of these drawbacks with a compact, general set of inputs that adequately describe the likely network reliability. We computationally demonstrate both the precision of the neural network estimate of reliability, and the ability of the neural network model to generalize to a variety of network sizes, including application to three actual large scale communications networks.Item A cross entropy approach to design of reliable networks(2009) Dengiz, Berna; Altiparmak, Fulya; 0000-0003-1730-4214; AAF-7020-2021One of the most important parameters determining the performance of communication networks is network reliability. The network reliability strongly depends on not only topological layout of the communication networks but also reliability and availability of the communication facilities. The selection of optimal network topology is an NP-hard problem so that computation time of enumeration-based methods grows exponentially with network size. This paper presents a new solution approach based on cross-entropy method, called NCE, to design of communication networks. The design problem is to find a network topology with minimum cost such that all-terminal reliability is not less than a given level of reliability. To investigate the effectiveness of the proposed NCE, comparisons with other heuristic approaches given in the literature for the design problem are carried out in a three-stage experimental study. Computational results show that NCE is an effective heuristic approach to design of reliable networks. (C) 2008 Elsevier B.V. All rights reserved.Item A Mathematical Formulation And Heuristic Approach For The Heterogeneous Fixed Fleet Vehicle Routing Problem With Simultaneous Pickup And Delivery(2021) Kececi, Baris; Altiparmak, Fulya; Kara, Imdat; ABH-1078-2021This study considers a variant of the vehicle routing problem (VRP) called the heterogeneous VRP with simultaneous pickup and delivery (HVRPSPD). The HVRPSPD may broadly be defined as identifying the minimum cost routes and vehicle types. To solve the HVRPSPD, first, we propose a polynomial-size mixed integer programming formulation. Because the HVRPSPD is an NP-hard problem, it is difficult to determine the optimal solution in a reasonable time for moderate and large-size problem instances. Hence, we develop a hybrid metaheuristic approach based on the simulated annealing and local search algorithms called SA-LS. We conduct a computational study in three stages. First, the performance of the mathematical model and SA-LS are investigated on small and medium-size HVRPSPD instances. Second, we compare SA-LS with the constructive heuristics, nearest neigh-borhood and Clarke-Wright savings algorithms, adapted for the HVRPSPD. Finally, the performance of SA-LS is evaluated on the instances of the heterogeneous VRP (HVRP), which is a special case of the HVRPSPD. Computational results demonstrate that the mathematical model can solve small-size instances optimally up to 35 nodes; SA-LS provides good quality solutions for medium and large-size problems. Moreover, SA-LS is superior to simple constructive heuristics and can be a preferable solution method to solve HVRP and VRPSPD instances successfully.Item Multiple Service Home Health Care Routing and Scheduling Problem: A Mathematical Model(2020) Dengiz, Asiye Ozge; Atalay, Kumru Didem; Altiparmak, FulyaThe home health care routing and scheduling problem (HHCRSP) is an extension of the vehicle routing problem (VRP) that are scheduled and routed to perform a wide range of health care services. Nurses, doctors and/or caregivers provide these services at patients' home. In this study, a mathematical model for HHCRSP is presented. The model is extended to take into account additional characteristics and/or constraints based on specific services, patient needs. In the home health care (HHC) problems, services that must be performed simultaneously or within a convinced time are undoubtedly very important. Thus, we consider several numbers of services, skill requirements for the care workers and time windows. Generally, the main aim of the HHC problems is minimizing the travelling distance as well as maximizing the patients' satisfaction. Thus, the model in this study contains both of these objectives taking into account several measurements.