A two-stage optimization model proposal for minimizing internal logistics costs

ABSTRACT Coşkun, Ş. (2025). A Two-stage Optimization Model Proposal for Minimizing Internal Logistics Costs (Doctoral Thesis). Sakarya University. In today's competitive production environment, the sustainable success of companies depends not only on the development of production technologies but also on the effective management of logistics processes. In this thesis, an integrated optimization model has been developed to solve the cost, time and energy efficiency problems that arise in the internal logistics processes of manufacturing enterprises. In the study, a holistic model is proposed as an alternative to piecemeal solution approaches by integrating warehouse layout and vehicle selection decisions, which are the two main elements of internal logistics. In the literature, these two decision-making areas are usually treated independently and with fixed parameters; this is not sufficient to reflect the complex structure in real production environments. The proposed model is designed as a flexible and multi-criteria structure that can adapt to changing conditions. A comprehensive evaluation framework is created by integrating multiple performance criteria such as transportation time, distance, energy consumption, cost and labor utilization into the decision structure of the model. Thus, in addition to being a unique example of modeling from an academic point of view, the developed system offers a highly applicable solution in the manufacturing sector and provides guidance to decision makers. The warehouse slotting model, which constitutes the first stage of the model, aims to place materials on shelves within the warehouse in a way that minimizes transportation distances to the relevant production and assembly areas. The main objective of this stage is to facilitate material flow, optimize transportation routes within the warehouse and increase the overall efficiency of the system by reducing operational complexity in the warehouse area. Shelf placement decisions are made by taking into account many parameters such as the physical distance to the production locations where the materials are requested, the current occupancy status of the shelves and door connections; thus minimizing transportation time and labor requirements. This model ensures that material movements within the warehouse are more predictable, organized and strategic. The second stage, the vehicle selection model, aims to decide which vehicle to use in the transportation operations to be carried out in the production and assembly sites in accordance with the shelf layout structure determined in the first stage. This model includes various transportation vehicles such as forklifts, pallet trucks and material handling trolleys; issues such as load capacity, energy consumption, transportation speed, labor costs, compatibility of raw materials and transportation vehicles are evaluated by considering multi-criteria performance criteria. In this way, the most appropriate vehicle type is selected for each transportation task, ensuring energy efficiency and reducing overall costs. Both modules are mathematically structured using linear programming methods and integrated to feed each other. This structure ensures that decisions are made with a system-wide approach, ensuring efficiency not only at the local level but also at the global level. In the application phase of the study, real field data obtained from a medium-sized manufacturing company operating in Sakarya province and working with integrated processes in the production site was used. The data set obtained from the field survey includes detailed analysis of technical information on warehouse doors, racking systems, production and assembly lines, and transportation vehicles. The scope of the study is limited to field data from a specific manufacturing facility and the model does not include dynamic warehouse structure or real-time variables. Therefore, the validity of the study is limited to the conditions of the facility in question, and no generalizations are made for dynamic variables in different scenarios. During the implementation process, three scenarios (balanced, partially flexible and flexible) were created reflecting different operating conditions; each of them was subjected to distance and cost-based performance evaluations. The results of the analysis showed that flexible packaging and transportation strategies resulted in improvements of up to 15% in total transport distance and up to 10% in energy consumption and logistics costs. Thus, the model is not only a theoretical proposal, but also a practical solution that can be applied in the field and directly help decision makers. In this context, the study contributes to the comprehensive optimization of internal logistics. It also has the potential to simultaneously improve multidimensional performance criteria such as cost, time and energy in the manufacturing sector. Future studies are recommended to focus on dynamic warehouse systems, real-time data integration and optimization approaches under uncertainty. Keywords: Internal logistics, warehouse optimization, vehicle selection, mathematical modeling, slotting, energy efficiency, production systems.