Yazar "Erol, Rizvan" seçeneğine göre listele

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    A Novel Hybrid Artificial Intelligence Based Methodology for the Inventory Routing Problem
    (Mdpi, 2019) Boru, Asli; Dosdogru, Ayse Tugba; Gocken, Mustafa; Erol, Rizvan
    In this paper, a new hybrid method including simulation optimization and artificial intelligence based simulation is created to solve the inventory routing problem (IRP) in which three different routing strategies are evaluated for uneven demand patterns including intermittent, erratic, and lumpy demand. The proposed method includes two phases. In the first phase, a nondominated sorting genetic algorithm II based simulation is employed to perform a multi-objective search for the IRP where the objectives of the method are total supply chain cost minimization and average service level maximization. In the second phase, artificial neural network based simulation is used to adjust the reorder point and order-up-to-level by forecasting the customer demand at each replenishment time. The results of the study demonstrated that the average service level is at least 98.54% in the supply chain. From this, it can be concluded that the proposed method can provide a tremendous opportunity to improve the average service level under uncertain environments. In addition, it is determined that different routing strategies can be selected for different demand patterns according to the considered performance measures.
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    Öğe
    Capacity Optimization in Dynamically Routing Computer Network Systems
    (Univ North, 2022) Uncu, Nusin; Erol, Rizvan
    A computer network system is a complex system with a great number of dynamic components. There are many devices in the system, such as computers, routers, lines, hubs, and switches. In addition to these hardware systems, many protocols are integrated to set the rules and provide the way of communication. Due to the nature of the system, it is hard to formulate and solve problems analytically without making any assumptions. One of the prominent problems that occur in computer systems is the line capacity assignment problem. In the previous mathematical models, message routes were predetermined and the dynamic nature of the system was neglected. This study deals with the line capacity assignment problem under a dynamically routing policy. Four different computer network topologies are used and solved by two heuristic algorithms via simulation. A dynamic search approach based on the occupancy rate of lines is used to define the consecutive routes of messages. The performances of harmony search and genetic algorithms via simulation are compared with the results of OptQuest, one of the optimization packet programs embedded in simulation software Arena (R).
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    Öğe
    PSO based approach for scheduling NPD projects including overlapping process
    (Pergamon-Elsevier Science Ltd, 2015) Koyuncu, Esra; Erol, Rizvan
    The efficient scheduling of the new product development (NPD) projects is important to reduce the required development time, and to offer the new product faster. Activity overlapping is commonly regarded as the most promising strategy to reduce product development times. However, overlapping must be well-planned by weighting the gain from the activity overlapping against the additional time for rework. The objective of this research was to develop a resource constrained scheduling methodology for NPD projects considering overlapping of activity couples. A particle swarm optimization based approach is used to schedule NPD projects that include overlapping process. The proposed PSO method is developed into a user friendly system so that the practitioners can utilize it. A real-life example of a product development project taken from the literature is used to show the efficiency of the software. (C) 2015 Elsevier Ltd. All rights reserved.