Araç rotalama ve çok boyutlu yükleme problemlerine entegre bir yaklaşım

In this thesis, in the context of the transportation of goods, we propose a set of algorithms regarding real combinatorial optimization problems called The Three-Dimensional Loading Capacitated Vehicle Routing Problems (3L-CVRP). The 3L-CVRP is an integrated routing problem combining two well-known optimization problems, Vehicle Routing Problem (VRP) and Container Loading Problem (CLP). This problem is solved by two main approaches: Constraint Programming (CP) and a new elitism-based Evolutionary Algorithm (EA). The former approach employs constraints for reducing the set of values each variable can assume, and we present a first CP strategy for this problem via varied constructive techniques aiming for optimal solutions. The latter method involves an Evolution Strategy heuristic, which is a subfield of EA. Elitism serves as an operational feature of Evolutionary Algorithms (EAs) that effectively reduces genetic drift. It works by allowing the most competent individuals in the population to pass on their traits to the following generation. Additionally, we enhance the traditional 3L-CVRP version by incorporating additional loading constraints to tackle pickup and delivery problems. All proposed methods underwent implementation and experimental testing. To ensure precision and clarity, a comprehensive suite of computational tests was executed using numerous benchmark instances. When required, both large and small benchmark instances were adapted to evaluate model quality. All the results obtained have subsequently been presented and discussed.