An Effective Logistics Network Design Using Donkey-Smugglers Optimization (DSO) Algorithm

Abstract

Logistics means management of goods transportation from one place into another in an effective way. Most of the logistic companies is very effective in transportation of goods through proper design of logistics network. When the logistics network design is effective, then the delivery of goods to the right place at right time is effective. In general travelling salesman problem (TSP) supports to design logistics network and plays a vital role in effective logistics management. Hence, solving TSP in polynomial time will greatly influences the proper design logistics network. As a result the delivering of goods will be very effective. Thus the objective of this project is to solve TSP using optimization algorithm in order to design an effective logistics network. Many researchers have proposed different kinds of optimization algorithms to solve NP hard problem TSP. But still there is a need to solve TSP in polynomial time and also to handle uncertainty situation. Thus the aim of this project is to use adaptive based Donkey-Smugglers optimization (DSO) algorithm to solve TSP problem in polynomial time and handle uncertainty events in more effective. The salient feature of this proposed system is able to handle uncertainty situation with the help of adding adaptive part in DSO algorithm to reduce time delay in delivery of goods. Since logistics network is heavily depends upon time, traffic, load weight, competency of driver etc. Hence there is a possible for uncertainty happens during delivering of goods. In order to handle this uncertainty situation, the project aims to solve TSP problem using adaptive based DSO algorithm. Meanwhile the proposed system also compares the results with other adaptive optimization algorithms namely Genetic Algorithm (GA) and Ant Colony Optimization (ACO). The results have been proved that the Adaptive based DSO algorithm works well even in uncertainty situation and able to solve TSP in polynomial time. As well as the proposed system achieves minimum average time taken even when there is large number of instances. Hence the proposed system reduces time delay effectively and helps to deliver goods at right place at right minimum time.