The rapid and efficient deployment of unmanned aerial vehicles (UAVs) in post-disaster scenarios is recognized as critical for effective management and logistics. The problem of selecting the most suitable UAVs for three key tasks—monitoring, light load transportation, and heavy load transportation—is addressed in this study. An extensive review of related literature was conducted to identify specific evaluation criteria tailored to each task. The UAV evaluation problem has been divided into three sub-problems, and an integrated multi-criteria decision-making (MCDM) approach is proposed within a Pythagorean Fuzzy environment for evaluation. The Step-Wise Weight Assessment Ratio Analysis (SWARA) method was employed to determine criteria weights. To rank UAVs currently available on the market, the Evaluation Based on Distance from Average Solution (EDAS) and Combinative Distance-based Assessment (CODAS) techniques were applied, with the Copeland Score used to aggregate and finalize the ranking based on each UAV’s overall performance across criteria. The results highlight key UAV choices for each task, guiding decision-makers toward UAVs that best meet the specific operational needs of post-disaster logistics. This framework provides a robust, adaptable tool for enhancing the agility and effectiveness of disaster response strategies through informed UAV selection.

Tr en Bu çalışmada, bir ecza deposunun günlük sipariş toplama stratejisi incelenmiş ve uygun bir yaklaşım geliştirilmiştir. Ürünlerin ve siparişlerin hacimsel olarak küçük olduğu, toplayıcı kapasitesinin göreceli olarak büyük olduğu depolar için uygun olan, sipariş yığınlama stratejisi kullanılmıştır. Günlük siparişler, siparişler arası ilişkiyi en büyükleyen bir matematiksel modelin yardımıyla sipariş yığınlarına ayrılmış. Birden çok siparişin bir araya gelmesiyle oluşan yığınlar içerisinde benzer ürünleri içeren siparişler bulunduğu için toplama sırasında ki kayıp zaman ve mesafeden tasarruf sağlanacaktır. Matematiksel modelin kesin çözümünün zaman alması nedeniyle genetik algoritma kullanılarak sonuç üretilmiştir. Farklı toplama stratejileri sonucunda kat edilen toplam mesafe benzetim yardımıyla hesaplanarak, istatistiki olarak sonuçların güvenilirliği ve performansları sonuç bölümünde tartışılmıştır. In this study, daily strategy of order picking is examined and proposed a new approach in a pharmacy warehouse. If the goods and orders are relatively small for the picker’s capacity, the order batching strategy should put to use. Daily orders was divided to order batches using mathematical model maximised the relationship among the orders. The order batches which are consist of more than one orders save up time and distance during the order picking period. Optimum solution of mathematical model take up time so that Genetic algorithm is used for order batching problem. Travelled the total distance is simulated in existing and batching strategy, the confidingness and performance of the results are tested statistically and argued in conclusion.

The Covid-19 pandemic has significantly impacted consumer behavior and commerce, prompting a shift towards online goods and services. The surge in demand has led to inefficiencies and disruptions, especially in the last-mile delivery (LMD) process. Because of the LMD, the final stage of the supply chain, plays a crucial role in transporting goods from businesses to consumers, challenges such as the cost inefficiencies of direct home delivery have underscored the need for innovative solutions. In this study, the collection delivery points (CDPs) approach was adopted instead of direct home delivery. It focuses on addressing these challenges by adopting service points as dynamic CDPs and handling the problem as a dynamic location routing problem (DLRP). Two solutions approaches are proposed, to select candidate depots strategically and determine efficient route configurations, to aim to minimize travel distance. One of them is a two-phased hierarchical method that starts with clustering and continues with an Ant Colony Optimization (ACO) based-hybrid algorithm, and the other one is based solely on an ACO-based hybrid algorithm. The performance of these approaches is evaluated on modified benchmark instances from the literature. It has been observed that the ACO based-hybrid algorithm is more successful in terms of total travel distance, and if an evaluation is made in terms of the number of routes, it is recommended that the results of the two-phased hierarchical method should also be considered. Furthermore, a real word case study was conducted with the proposed methods and the results were compared from different perspectives. The results corroborate the findings regarding benchmark instances, thereby providing additional validation to the results obtained.