greedy algorithm

This paper presented greedy algorithm for solving student allocation problem that has arisen in internship program. In internship program, engineering students stay one semester in industries which are located across the country and teachers visit students once/twice for supervision during the program. As the industries scatter across the country, teachers spend long time on travel. And this results in wastage of teachers working time and money spent for transport. Therefore, allocating students to universities near the internship location extensively reduces the transport time and money spent for transport. For the current study, we consider 4th mechanical engineering students who are currently working in the industry. The proposed approach extensively decrease the distance traveled from 23,210 km to 2,488.8 km and the time spent on the road from 397 hrs. 40 min to 51 hrs. 30 min. and finally, the results obtained from the greedy algorithm is compared with other heuristics (i.e., Genetic algorithm and Particle swarm optimization) and the greedy algorithm outperforms the other methods.

Transportation in economic systems such as services, production and distribution enjoys a special and important position and provides a significant portion of the country's gross domestic product. Improvements in transportation system mean improvements in the traveling routes and the elimination of unnecessary distances in any system. The Vehicle Routing Problem (VRP) is one of the practical concepts in the field of investigation and many attempts have been made by researchers in this area. Due to the importance of transportation issues in the real world and the status of these issues in the types of existing systems. In this paper, we investigate the Vehicle Routing Problem with Time Window (VRPTW) and provide a solution for it. The problem of routing vehicles with a time window is an extension of the problem of routing vehicles with limited capacity (CVRP) in which servicing must be done in a specific time window. The purpose of this problem is to optimize the route for each vehicle so as to minimize the total cost of the route and the number of vehicles used, and ultimately maximize customer satisfaction. In the paper, a hybrid method based on cuckoo search and greedy algorithm is proposed to solve the problem of VRPTW. For the cost function, different criteria have been used that are within the framework of the VRPTW problem within hard and soft constraints. In order to evaluate the proposed method, the dataset is used in different sizes. The proposed method is significantly higher compared to similar methods.