Browsing by Author "Alim, Muzaffer"

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Batch Ordering Inventory Management Under the Mixed Demand Information: a Case Study
(Konya Technical University, 2020) Alim, Muzaffer; Beullens, Patrick
This study is concerned with analysing the past demand data and development of aninventory model with demand arising from deterministic which is known in advance and random sourcessimultaneously. Two different shortages are created for each demand type and in order to prevent modelto backlog the deterministic demand, very high shortage cost is given for deterministic demand. Thenumerical value of the parameters are obtained from a real case which the inventory system of aninformation and technological organization of a university. The main difference of this study from theprevious studies is that the order amount must be in palette quantity for a deterministic and stochasticdemand inventory problem. Under this constraint, an inventory model is developed and tested withseveral datasets. Assuming lead time as constant, the value of deterministic demand present in the systemand impact of palette constraint are investigated. These investigations are compared with the status quoin the case study. It has seen that the palette quantity behaves as safety stock for high level randomdemand. Recommendations based on the impacts of advance demand information, lead time and palletquantity are presented in terms of changing in ordering costs, holding costs and service level.
Citation - WoS: 3
Citation - Scopus: 4
Investigating the Effects of Various Control Measures on Economy and Spread of Covid-19 in Turkey: a System Dynamics Approach
(Sage Publications Ltd, 2022) Alim, Muzaffer; Kesen, Saadettin Erhan
The coronavirus disease 2019 (COVID-19) which began in Wuhan in December 2019 has permeated all over the world in such a short time and was declared as a pandemic by World Health Organization (WHO). The pandemic that is erupting all of a sudden attracts the researchers to examine the spread and effects of the disease as well as the possible treatments and vaccine developments. In addition to the analytical models, such as compartmental modeling, Markov decision process, and so on, simulation and system dynamics (SD) are also widely applied in this field. In this study, we adopt the compartmental modeling stages to build an SD approach for the spread of the disease. A dynamic control measure decision support system (DSS) that varies depending on the number of daily cases is incorporated to the model. Furthermore, the economic loss in the gross domestic product (GDP) and workforce due to hospital stay and death caused by the COVID-19 are also investigated. The model is tested with various numerical parameters and the results are presented. The results on the spread of the disease and the associated economic loss provide meaningful insights into when control measures need to be imposed at which level. We also provide some policy insights, including some alternative policies, such as increasing awareness of people and vaccination in addition to control measures. The results reveal that the total number of cases and deaths is approximately 37% higher in the absence of dynamic DSS. However, everything comes at a price and applying such control measures brings about an increase in the economic loss about 47%.
Citation - WoS: 3
Citation - Scopus: 4
Solution Approaches for Mixed Pallet Collection Problem: a Case Study in a Logistic Company
(YILDIZ TECHNICAL UNIV, 2019) Kesen, Saadettin Erhan; Alim, Muzaffer
In this paper, we study a mixed pallet collection problem in a warehouse of the company operating in fast moving consumer goods industry and present a mixed integer programming formulation with the objective function of total travelling distance minimization. The problem studied is shown to be equivalent to the well-known vehicle routing problem. Since the problem belongs to the class of NP-hard problems, introduced mathematical formulation cannot provide optimal solution in an acceptable amount of time. We, therefore, develop an algorithm based on Simulated Annealing (SA) meta-heuristic approach to find near-optimal solution in a quite shorter computational time. Routes are constructed using Clarke&Wright saving algorithm and then these routes are perturbed whereby three neighborhood operators, namely swap, insert, swap-range are utilized to further improve the quality of the solution. Experimental results based on a real case instance demonstrates that SA algorithm is capable of providing solution more quickly than that of CPLEX solver but the quality of the solution found by SA is 7% worse than that of CPLEX.