Endüstri Mühendisliği Bölümü / Department of Industrial Engineering
Permanent URI for this collectionhttps://hdl.handle.net/11413/6819
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Browsing Endüstri Mühendisliği Bölümü / Department of Industrial Engineering by Type "Book chapter"
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Publication An analytical approach for analysing the impact of risks on production planning: Case of Öztiryakiler(2020) Telatar, E.; Bekeç, T.; Başaran, A.; Balıkçı, N.; Bilgin, B.; İlbay, E.; AKTİN, AYŞE TÜLİNAccurate and applicable production plans are a must for manufacturing companies. Although companies tend to prepare ideal production plans, some exogenous factors can affect their validity. These risks, which occur unexpectedly, will have a negative influence on the plan. This study aims to determine the exogenous factors affecting the success of production planning of square and rectangular food containers manufactured by Öztiryakiler, and analyse their impacts on the plans. The risk factors are evaluated using Failure Mode and Effects Analysis, and their risk priority numbers are calculated. A mixed-integer linear programming model with the objective of total cost minimisation is developed to obtain the production plan of containers. Initially, an ideal data set is used as input; hence, this model’s output displays a risk-free plan. Similarly, for each of the risk factor scenarios, mathematical models are solved with risk-related data. GAMS software and CPLEX solver is utilised in the solution of all models. Finally, for each of the selected high risk alternative, the expected total costs are calculated. This is achieved by multiplying the normalized risk priority number obtained from the Failure Mode and Effects Analysis with the corresponding optimal total cost of the risky plan. This analysis highlights the most critical risks, and comparison with the risk-free plan helps in proposing system improvements. © 2020, Springer Nature Switzerland AG.Publication Fuzzy C-Means Algorithm with fixed cluster centers for uncapacitated facility location problems: Turkish case study(2014) Esnaf, Şakir; Küçükdeniz, TarıkIn this study, a new algorithm to solve uncapacitated facility location problems is proposed. The algorithm is a special version of original fuzzy c-means (FCM) algorithm. In FCM algorithm, unlabeled data are clustered and the cluster centers are determined according to priori known stopping criterion iteratively. Unlike the original FCM, the proposed algorithm allows the unlabeled data are to be assigned with single iteration to related clusters centers, which are assumed to be fixed and known a priori like location of facilities according to their degrees of membership. First, the proposed algorithm is applied to various benchmark problems from literature and compared with integer programming. Second, the proposed algorithm is tested and compared with particle swarm optimization (PSO) and artificial bee colony optimization (ABC) algorithms based uncapacitated facility location method on alternative versions such as discrete, continuous, discrete with local search and continuous with local search in literature for a Turkish fertilizer producer's real data. Numerical results obtained from real life application show that the proposed algorithm outperforms the PSO-based and ABC-based algorithms.