نوع مقاله : مقاله پژوهشی

نویسندگان

• حسین اعتمادفرد ¹
• حامد خرقانی ²
• مهدی نجاریان ²
• روزبه شاد ³

¹ استادیار گروه مهندسی عمران، دانشکده مهندسی، دانشگاه فردوسی، مشهد، ایران

² دانشجوی کارشناسی ارشد سیستم اطلاعات مکانی (GIS)، گروه مهندسی عمران، دانشکده مهندسی، دانشگاه فردوسی، مشهد، ایران

³ دانشیار گروه مهندسی عمران، دانشکده مهندسی، دانشگاه فردوسی، مشهد، ایران

چکیده

امروزه مدیریت شبکه‌های توزیع مواد غذایی با هدف پاسخ‌گویی سریع به تقاضای مصرف‌کنندگان، کاهش هزینه توزیع و افزایش سود در مقایسه با رقبای تجاری اهمیت بسیاری یافته است. فروشگاه‌های “شهرما” شبکه گسترده توزیع محصولات کشاورزی در شهر مشهد هستند که با هدف عرضه مستقیم محصولات کشاورزی و فراهم نمودن امکان دسترسی ارزان و سریع‌تر شهروندان به میوه و تره‌بار شکل گرفته‌اند. در این مقاله، مسیرهای توزیع بهینه و به موقع محصولات فروشگاه‌هایی با نام تجاری “شهرما” از مبدأ تا میدان میوه و تره‌بار مورد بررسی قرار می‌گیرد. به این منظور از ‌الگوریتم‌های تکاملی ژنتیک و ازدحام ذرات برای بهینه کردن زمان توزیع استفاده شده است. برای توزیع عادلانه و به موقع محصولات میان تمام فروشگاه‌ها یک قید زمانی سه ساعته وارد مسئله شده است. به این معنی که اگر توزیع میان تمام فروشگاه‌ها در زمان کمتر از سه ساعت صورت نگیرد به تعداد یک وسیله نقلیه توزیع جدید به مسئله اضافه خواهد شد. این افزایش تعداد وسایل نقلیه تا جایی ادامه پیدا خواهد کرد که توزیع میان تمام فروشگاه‌ها کمتر از سه ساعت صورت پذیرد. به‌منظور تعیین زمان مسیر میان فروشگاه‌ها بر روی شبکه راه‌های شهر مشهد از آنالیز شبکه در نرم‌افزار ArcGIS استفاده شده است. در انتها دو الگوریتم ژنتیک و ازدحام ذرات توانستند توزیع میوه و تره‌بار را با چهار وسیله نقلیه انجام دهند. مقایسه نتایج دو الگوریتم نشان می‌دهد که مجموع زمانی توزیع در الگوریتم ژنتیک در مقایسه با الگوریتم ازدحام ذرات 47 دقیقه کمتر بوده و الگوریتم ژنتیک، مسیرهای بهتری را برای توزیع پیشنهاد داده است.

کلیدواژه‌ها

• بهینه‌سازی مسیر
• الگوریتم ژنتیک
• الگوریتم ازدحام ذرات
• سیستم اطلاعات مکانی (GIS)

موضوعات

• سیستم اطلاعات جغرافیایی

عنوان مقاله [English]

Spatio-Temporal estimation of optimal distribution path for perishable materials with evolutionary algorithms - Case study: Fruits and Vegetables

نویسندگان [English]

• Hossein Etemadfard ¹
• Hamed Kharaghani ²
• Mahdi Najjarian ²
• Rouzbeh Shad ³

¹ Assistant Professor, Civil Engineering department, Engineering faculty, Ferdowsi University of Mashhad, Mashhad, Iran

² M.Sc. Student of GIS, Civil Engineering department, Engineering faculty, Ferdowsi University of Mashhad, Mashhad, Iran

³ Associate Professor, Civil Engineering department, Engineering faculty, Ferdowsi University of Mashhad, Mashhad, Iran

چکیده [English]

Extended Abstract
Introduction:
The increasing demand for sustainable food consumption as well as the change in the consumption pattern has led to efforts to improve the food distribution process. This is to speed up service delivery and prevent the spoilage of perishable materials. Among the most significant topics in the food supply chain is perishability, a phenomenon that occurs in certain categories of products such as fruits, vegetables, and dairy products. Perishability refers to the property in which a product loses its commercial value and usability after a certain period. However, meeting the general needs of citizens, especially the supply of food, is one of the most significant axes of urban service activities on the city's economic platform. In addition, the provision of comfort and well-being for residents depends on the proper establishment, optimal distribution, and sufficient variety of products offered in shopping centers. Day markets as well as fruit and vegetable fields provide fast and appropriate daily needs for residents. In addition, choosing fast and reliable routes for food distribution in the city is one of the other significant and influential factors in providing quality services. It should also be noted that in vehicle routing problems (VRP) related to food products, routes for vehicles must be created that match the schedules of some stores to deliver products.
Materials and Methods:
To optimize the fruit and vegetable distribution routes between the fruit and vegetable fields and Shahre-ma stores in Mashhad, this research will use genetic algorithms and particle swarm algorithms. This research will have the aim of optimizing distribution time, which was not addressed in previous research. This research presents its innovation by considering a three-hour time limit in the problem-solving algorithm. Genetic Algorithm (GA) is a learning method based on biological evolution and influenced by the hypothesized mechanism of natural selection in which the fittest individuals in a generation survive longer and produce a new generation. And in this article, it is implemented in such a way that the algorithm itself determines the most appropriate number of vehicles. The number of vehicles should be such that distribution among all stores is done in less than three hours and five minutes in each store. There should be a stop. And if distribution among all stores is not done in less than 3 hours, a new vehicle will be added to the number of vehicles. Also, particle swarm optimization (PSO) is a technique inspired by the behavior of birds when searching for food. In this research, the data collected include the location of Shahre-ma stores and the fruit and vegetable square in Mashhad city. These data were prepared from the information of Mashhad municipality. Also, to implement these algorithms, MATLAB software has been used. Network analysis has been done to determine the distance between Bar Square and Shahre-ma stores in ArcGIS software using network analysis.
Results and discussion:
This research proposes several hypotheses, including that the maximum optimal time is 3 hours and products should be distributed by 7 am in all places. Also, city traffic is uniform from 4 to 7 in the morning and the same product package is distributed in all stores. Comparing the results of two genetic algorithms and particle swarm shows that the genetic algorithm has a higher efficiency in optimizing the distribution path of fruits and vegetables. Because the time of the four routes derived from the genetic algorithm is approximately 92 minutes, 84 minutes, 80 minutes, and 82 minutes respectively. The total length of all routes is 127 km and 779 meters and the total time of all routes is 338 minutes. And the time of the four routes obtained from the particle swarm algorithm is approximately 102 minutes, 103 minutes, 89 minutes, and 91 minutes respectively. The total length of all routes is 175 km and 390 meters and the total time of all routes is 385 minutes. And in total, the times obtained for four vehicles in the genetic algorithm were 47 minutes less than the particle swarm algorithm. In addition, the total length of the paths in the genetic algorithm was 47 km and 611 meters less than the particle swarm algorithm.
Conclusion
The genetic algorithm was able to achieve the optimal solution by evaluating the objective function 12,000 times. This is 2,900,000 in the particle swarm algorithm. Accordingly, the time required to reach the optimal solution differs significantly between the two algorithms.

کلیدواژه‌ها [English]

• Path optimization
• Genetic algorithm
• Particle swarm algorithm
• Geospatial Information System (GIS)