Planning Route Distribution of Ikm DM Using the Methods Vehicle Routing Problem (VRP) and Shortest-Route Algorithm (original) (raw)
Related papers
2018
 The problem of distribution of goods of PT REHAU Indonesia is a problem of Vehicle Routing Problem (VRP) which is the problem of finding an effective and efficient route from a depot to a scattered customer. This research tries to analyze nearest neighbor method in solving the problem. This research will use quantitative method with 7 delivery route as samples involving 30 location points and 900 matrix of distance between locations. Data collection was done by conducting field study, ie observation and tracing of secondary data. This study uses a causal associative method of research that aims to determine the causal relationship (causal) or is influential between two or more variables. The results of this study indicate that the method is able to reduce total mileage by 15% from 1,614 km to 1,372 km or decrease as much as 242 km, reduce the delivery time of 16% or as much as 7 hours 49 minutes, and reduce the cost of delivery as much as 16% or decreased as much Rp 689,718.
Journal Industrial Servicess
PT X is a manufacturing company that produces motorcycle units. With the continuous increase of product demand from consumers, it makes PT X being one of the largest manufacturing companies in Indonesia. Currently, the distribution route is determined by PT X only based on the experience and knowledge of the drivers. The distribution route should include the configuration of the appropriate distribution channels, in order for the delivery to be fast at a low cost. This problem is known as the vehicle routing problem (VRP). To overcome the problem must conduct research in the hope to minimize the cost of distribution of motorcycle units to the dealers, that is by calculating fuel consumption, tolls chargers, bundles of units and loading and unloading. The problem is solved by using saving matrix method. The result can minimize distribution costs of Rp3,323,500 compare with the actual cost of the company is Rp3,530,000. So it can be seen that there is a decrease in the cost of Rp206,500/day.
Perishable items such as food products, vegetables, flowers, ready-mixed concrete, blood and etc. are usually destroyed during production and delivery process, so to prevent spoilage of such products, these products must reach the customer at the appropriate time to the manufacturers. One of the effective factors in the timely delivery of various products to the customer is the choice of the optimal delivery route, which is referred to as the issue of vehicle routing. The issue of vehicle routing for the distribution of various products is one of the most widely used issues in the field of operations research, which is very useful in planning the transportation fleet. In this Research, we seek to determine the operational plan of homogeneous vehicles with limited capacity to send products from the central warehouse to a group of customers that are geographically dispersed in different areas, so that the number of vehicles and travel costs are minimized. Most existing studies on decision-making issues have assumed the issue in an environment of conclusive data. However, in many cases it is observed that it is difficult to determine the exact values for the parameters and the values must be fuzzy. As a result, one of the most important decisions to be made in the supply chain is the issue of efficiency and effectiveness of this chain along with parameters and variables with uncertainty. Uncertainty in the supply chain leads to non-optimization of decisions made on the assumption of uncertainty, so to match the uncertainty, some problem parameters such as travel time, shipping cost, as well as the start and end of customers' time windows in the chain Supplies are considered as fuzzy numbers. Due to the fact that the mentioned problem is a very complex problem and for its large dimensions we cannot find a suitable quality answer in a short time with accurate methods, so to solve this model on a smaller scale, Gams software has been used. Finally, to show the application of the proposed model in the real world, the issue of product distribution among customers in the Ports and Maritime Organization of Gilan Province (Bandar Anzali) has been investigated, which shows that distributors can use this method to reduce their operating costs.
optimization of goods distribution route.pdf
OPTIMIZATION OF GOODS DISTRIBUTION ROUTE ASSISTED BY GOOGLE MAP WITH CHEAPEST INSERTION HEURISTIC ALGORITHM (CIH), 2018
Abstract - In the distribution of goods, the efficiency of goods delivery one of which was determined by the path that passed to deliver the goods. The problem of choosing the shortest route was known as the Traveling Saleman Problem. Traveling Salesman Problem (TSP) was a classic problem trying to find the shortest route that possible salesmen who want to visit several cities without having to visit the same city more than once. To solve the problem of choosing the shortest route in the distribution of goods, the algorithm to be used was Cheapest Insertion Heuristic (CIH). This research was a qualitative research designed using case study method. This study aims to determine the minimum distance traveled by using the Cheapest Insertion Heuristics (CIH) algorithm. In this study, researchers took the route from the employee of Cahaya Bintang Printing and Advertising. Researchers determine the route and distance of each place visited by using google map. The concept in the Cheapest Insertion Heuristics (CIH) algorithm was to insert an unexpired city with an additional minimum distance until all cities are passed to get the solution of the problem. The step completion problem with Cheapest Insertion Heuristics (CIH) algorithm was: 1) search, 2) making subtour; 3) change the direction of the relationship, 4) repeat the steps so that all places are included in the subtour. Theoretically the total distance calculated using the CIH algorithm is 20.2 km, while the total distance calculated previously traveled with the ordered route is 25.2 km. There was difference of 5 km with the application of CIH algorithm. The difference between the distance certainly have an impact on the optimal distribution of goods to the destination. Therefore, CIH algorithm application can provide solution for determining the shortest route from distribution of goods delivery in Cahaya Bintang Printing and Advertising. Keyword : optimization, route, subtour, algorithm, graph
Location-inventory-routing Problem in a Context of City Logistics: A Case Study of Jakarta
Operations and Supply Chain Management: An International Journal
City logistics idea is to develop an effective, efficient, and environmentally friendly logistics system. The development of city logistics is related to energy consumption, traffic congestion, economic and environmental problems. As one of the megacities in the world, Jakarta faces an inventory problem which is low availability of only 76%. Jakarta also faces the problem of transportation that is traffic congestion. The problems show that it is needed to develop city logistics in Jakarta. City logistics developed in this paper is related to decisions of location, inventory, and routing problems or LIRP (location-inventory-routing problem) in short. The LIRP takes into account multi-products, multi suppliers, and traffic congestion as an external parameters. This paper aims to develop a heuristic method to solve the LIRP. The heuristic method is based on simulated annealing (SA) algorithm. Existing literature shows that this paper's heuristic method to solve the LIRP has never been developed before. From applying the heuristic method in Jakarta, the coordination concept of city logistics reduces the vehicle number by 73%, and the consolidation concept of city logistics increases the availability from 76% to 95%.
2015
Vehicle Routing Problem (VRP) is one of the most challenging problems in combinatorial optimization. Objective of VRP is to find minimum length route starts and ends in a depot. There are some additional constraints such as more than one depot, service time, time window, capacity of vehicle, and many more. These are cause of VRP variants. Vehicle Routing Problem with Time Windows (VRPTW) is a variant of VRP with some additional constrains, that are number of requests may not exceed the vehicle capacity, as well as travel time and service time may not exceed the time window. Multi Depot Vehicle Routing Problem (MDVRP) has number of depots serving all customers, a number of vehicles distributing goods to customers with a minimum distance of distribution route without exceeding the capacity of the vehicle. Many researches have presented algorithms to solve VRPTW and MDVRP. This article discusses solution characteristics of VRPTW and MDVRP algorithms, and their performance. VRPTW algori...
IOP Conference Series: Materials Science and Engineering, 2017
XYZ is a distributor of various consumer goods products. The company plans its delivery routes daily and in order to obtain route construction in a short amount of time, it simplifies the process by assigning drivers based on geographic regions. This approach results in inefficient use of vehicles leading to imbalance workloads. In this paper, we propose a combined method involving heuristic and optimization to obtain better solutions in acceptable computation time. The heuristic is based on a time-oriented, nearest neighbor (TONN) to form clusters if the number of locations is higher than a certain value. The optimization part uses a mathematical modeling formulation based on vehicle routing problem that considers heterogeneous vehicles, time windows, and fixed costs (HVRPTWF) and is used to solve routing problem in clusters. A case study using data from one month of the company's operations is analyzed, and data from one day of operations are detailed in this paper. The analysis shows that the proposed method results in 24% cost savings on that month, but it can be as high as 54% in a day.
Determination of the Fastest Path on Logistics Distribution by Using Dijkstra Algorithm
Proceedings of the 2nd International Seminar of Science and Applied Technology (ISSAT 2021), 2021
Dijkstra algorithm is one of the algorithms that is used to determine the path with the minimum total weight in the computer network, communication network, and transportation network problems. Some problems that have been studied using Dijkstra algorithm, namely multi-hop calibration of networked embedded system, achieving superior timing-driven routing trees and adaptive protection in microgrids. This article will determine the fastest path in the distribution of logistics by Bulog in West Java region by using Dijkstra algorithm manually and also by using Matlab. Data and information including the path connecting a warehouse to another Bulog warehouse will be used to build a connected weighted graph model. This data was obtained directly from Bulog office in West Java and through Google Maps application during the Covid-19 pandemic. Furthermore, path optimization is carried out by using Dijkstra algorithm, so that the fastest path tree is obtained. The fastest path tree is a path which edge set is a subset of the connected edge set of the connected weighted graph and has minimum total weight. Based on this optimization, the fastest path from Cibitung warehouse Bekasi to Bojong warehouse Cianjur is 154 minutes.
Vehicle routing optimization FOR ZAMZAM Company of Mashhad, Iran
Vehicle routing always be an important issue for companies in terms of cost. Therefore, detailed examination of this issue can reduce transportation costs and increase customer satisfaction and also raise the quality of management. Vehicle routing optimization is an NP hard and also spatial problem that will not be solved with exact solution, so some heuristics methods that support spatial feature is needed. ArcGIS 10.1 uses Dijestra to find shortest path and uses Tabu search heuristic algorithm for solving vehicle routing problem. This work by using ArcGIS 10.1 optimizes vehicle routing of ZAMZAM Company in case study of two zone; 5 and 6. In this article input data is divided into three categories; customer's data and constraints, vehicles data and constraints and company data and constraints. These three make up our geographical databases. Results show that routes and vehicles are 30 percent optimized. By applying these routes, cost function is reduced
IJLS, 2012
Distribution is the flow of products from the industry to retailers and to the end user. Distributing finished product from manufacturer to retailer is challenging problem in logistic management. The main objective in distribution is to deliver the product to destination with minimum travelling distance and total travelling time. PT XYZ is the garment company that distributes the products to its customer by its own. In determining the route, the route planned by PT. XYZ is not well organized. Therefore, the research proposed the program which combining the genetic algorithms (GA) methods and analytical hierarchy process (AHP) in order to solve multi objective function since the traditional genetic algorithms only find the single objective function. The weighting of AHP will be used in determining the fitness function of the chromosomes to produce the new population in GA. The fitness function includes the total traveling distance and total traveling time. By using GA-AHP in route planning, the optimization of time and distance is obtained finally.