Akademik Veri Yönetim Sistemi
International Congress of New Horizons in Sciences (INCOHIS 2023 SPRING), İstanbul, Türkiye, 20 - 21 Mayıs 2023, (Özet Bildiri)
Scheduling problems are a class of computational challenges that involve optimizing the allocation of resources or activities over time. These problems arise in various domains, including manufacturing, transportation, project management, and employee scheduling. The goal is to create an efficient schedule that minimizes costs, maximizes productivity by satisfying specific constraints. At their core, scheduling problems require assigning tasks or events to available resources while considering temporal and operational constraints. The constraints can include deadlines, resource availability, precedence relations, and capacity limitations. The objective may vary depending on the context. For example, in a manufacturing setting, the objective may be to minimize the total completion time, minimize the penalty cost or maximize the utilization of machines. In employee scheduling, the goal might be to minimize labor costs while ensuring adequate coverage. Scheduling problems can be classified into different types based on their characteristics and objectives. Some common types include job shop scheduling, project scheduling, vehicle routing, etc. Solving scheduling problems is computationally challenging due to the complexity of considering multiple constraints and finding optimal or near-optimal solutions. Various algorithms and optimization techniques, such as mathematical programming, heuristic algorithms, and metaheuristics, have been developed to address scheduling problems. By effectively solving scheduling problems, businesses and organizations can improve their operational efficiency, meet deadlines, optimize resource utilization, and ultimately enhance overall productivity. For this purpose, a hybrid heuristic algorithm consisting of taboo search and genetic algorithms is introduced in this study to optimize the scheduling problems.