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2 2022

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A combination K-means clustering and 2-opt algorithm for solving the two echelon e-commerce logistic distribution

Zuhanda Muhammad Khahfi, Suwilo Saib, Sitompul Opim, Mardiningsih Mardiningsih

LogForum

2022

Vol. 18, no. 2

213--225

Background: The rise of e-commerce in the community makes competition between logistics companies increasingly tight. Every e-commerce application offers the convenience and choices needed by the community. The Two-Echelon Vehicle Routing Problem (2E-VRP) model has been widely developed in recent years. 2E-VRP makes it possible for customers to combine shipments from several different stores due to satellites in their distribution stream. The aim of this paper is to optimize a two-echelon logistics distribution network for package delivery on e-commerce platforms, where vans operate in the first echelon and motorcycles operate in the second echelon. The problem is formulated as 2E-VRP, where total travel costs and fuel consumption are minimized. This optimization is based on determining the flow in each echelon and choosing the optimal routing solution for vans and motorcycles. Methods: This paper proposes a combination of the K-means Clustering Algorithm and the 2-opt Algorithm to solve the optimization problem. Many previous studies have used the K-means algorithm to help streamline the search for solutions. In the solution series, clustering is carried out between the satellite and the customer in the first echelon using the K-means algorithm. To determine the optimal k-cluster, we analyzed it using the silhouette, gap statistic, and elbow methods. Furthermore, the routing at each echelon is solved by the 2-opt heuristic method. At the end of the article, we present testing of several instances with the different number of clusters. The study results indicate an influence on the determination of the number of clusters in minimizing the objective function. Results: This paper looks at 100 customers, 10 satellites, and 1 depot. By working in two stages, the first stage is the resolution of satellite and customer problems, and the second stage is the resolution of problems between the satellite and the depots. We compare distance and cost solutions with a different number of k-clusters. From the test results, the number of k-clusters shows an effect of number and distance on the solution. Conclusions: In the 2E-VRP model, determining the location of the cluster between the satellite and the customer is very important in preparing the delivery schedule in logistics distribution within the city. The benefit is that the vehicle can divide the destination according to the location characteristics of the satellite and the customer, although setting the how many clusters do not guarantee obtaining the optimal distance. And the test results also show that the more satellites there are, the higher the shipping costs. For further research, we will try to complete the model with the metaheuristic genetic algorithm method and compare it with the 2-opt heuristic method.

Application of Clustering Method in Different Geophysical Parameters for Researching Subsurface Environment

Le Cuong Van Anh, Nguyen Ngan Nhat Kim, Nguyen Thuan Van

Inżynieria Mineralna

2022

no. 2

39--47

Safety of construction needs knowledge of physical parameters as stiffness or porosity of the subsurface environment. Combination of different geophysical methods such as electrical resistivity imaging and multichannel analysis of surface waves can provide distributions of resistivity and shear velocity which are responsible for the underground physical parameters. Their joint interpretation can solve individual problems of none-uniqueness of the solutions when expressing two inversion results to describe environment characteristics. In our work, the k-means clustering method can categorize the two parameters into specific zones that can help to interpret the geophysical data effectively. Our workflow consists of two stages in which two independent geophysical data are inverted and the k-means clustering is applied to the two results for achieving the specified groups. The collocated geophysical data are measured in District 9, Ho Chi Minh City, Vietnam. Matching with the geology drillhole information, the joint results generally present layered medium with the upper zone having smaller resistivity and shear velocity values and the bottom zone of stronger stiffness.

Bezpieczeństwo konstrukcji wymaga znajomości parametrów fizycznych, takich jak sztywność czy porowatość środowiska podpowierzchniowego. Połączenie różnych metod geofizycznych, takich jak obrazowanie rezystywności elektrycznej i wielokanałowa analiza fal powierzchniowych, może dostarczyć rozkłady rezystywności i prędkości ścinania, które są odpowiedzialne za parametry fizyczne podziemnych warstw. Ich wspólna interpretacja może rozwiązać indywidualne problemy niejednoznaczności rozwiązań przy wyrażaniu dwóch wyników inwersji do opisu cech środowiska. W naszej pracy metoda grupowania k-średnich może podzielić dwa parametry na określone strefy, co może pomóc w skutecznej interpretacji danych geofizycznych. Nasz przepływ pracy składa się z dwóch etapów, w których dwa niezależne dane geofizyczne są odwracane, a grupowanie k-średnich jest stosowane do dwóch wyników w celu uzyskania określonych grup. Zebrane dane geofizyczne są mierzone w Dystrykcie 9, Ho Chi Minh City, Wietnam. Dopasowując się do informacji uzyskanych z odwiertów geologicznych, wyniki połączeń ogólnie przedstawiają ośrodek warstwowy, w którym górna strefa ma mniejsze wartości rezystywności i prędkości ścinania, a dolna strefa ma większą sztywność.