Yazar "Gocken, M." seçeneğine göre listele

Listeleniyor 1 - 2 / 2
  • [ X ]
    Öğe
    INTEGRATING PROCESS PLAN AND PART ROUTING USING OPTIMIZATION VIA SIMULATION APPROACH
    (Daaam International Vienna, 2019) Gocken, T.; Dosdogru, A. T.; Boru, A.; Gocken, M.
    Determining the best process plan and route for each part is one of the main problems in dynamic stochastic systems. Therefore, multiple process plans are considered for each operation of each part (machine flexibility and/or part routing) and alternative operations (operation flexibility) simultaneously. In this paper, Optimization via Simulation (OvS) is utilized to plan the processes and route the parts in a dynamic stochastic flexible job-shop environment (DSFJS). Genetic algorithm (GA) which is envisaged to be the optimization component of OvS mechanism is integrated with the simulation model of the production system. A four-factor full factorial design is used to analyse the effect of main factors' and factor interactions' effects on the total of average flowtimes of each part performance of the shop. The design includes the flexibility level of the shop, number of parts, number of operations, and number of alternative process plans. Finally, the main findings of cases are summarized in the study.
  • [ X ]
    Öğe
    OPTIMIZATION VIA SIMULATION FOR INVENTORY CONTROL POLICIES AND SUPPLIER SELECTION
    (Daaam International Vienna, 2017) Gocken, M.; Dosdogru, A. T.; Boru, A.
    The need to explicitly select the best review model in inventory control system is greater than ever because managing and controlling inventories are difficult under intense competition. In this study, three important questions are answered in inventory control system: which review model (periodic or continuous) should be used; which objective function of review model should be used to increase competitiveness of the supply chain; how to find the optimal values of initial inventory, reorder point, and order-up-to level for each Distribution Centre (DC) and each Supplier. We proposed an Optimization via Simulation (OvS) approach to determine the best inventory control system with supplier selection and to obtain a remarkable amount of saving while increasing the competitive edge in a fully stochastic supply chain environment. According to the results, total supply chain cost can be improved at least 22 % and at most 66 % on average with proposed continuous review model.