Türk dağıtıcıların karşılaştığı zengin araç rotalama problemi için metasezgisel algoritmaların ve çözüm süreçlerinin araştırılması

Logistical challenges pose a substantial financial burden for distributors worldwide, particularly in light of escalating oil prices and evolving customer demands. This thesis addresses a Rich Vehicle Routing Problem (RVRP) encountered by a distributor in Turkey. The problem involves a multi-objective function that integrates road tariffs, specific customer constraints, and features observed in various VRP variants. Our study explores diverse solving approaches, including an exact method developed through a novel Mixed-Integer Linear Program, as well as non-exact solutions employing heuristic and metaheuristic algorithms. Notably, our findings highlight the efficacy of metaheuristic algorithms, particularly through a two-phase solving strategy: initially dividing and solving the problem into individual sub-problems, then integrating them comprehensively. The study concluded with a 5.13% reduction in operational costs compared to the distributor's existing plan, indicating significant potential for enhanced profitability while optimizing the daily scheduling of the vehicle fleet, and further expanding applications in operations research.