Applying Discrete Particle Swarm Optimization to Scheduling Deliveries and Services of Large-Sized Televisions

• Main Author: 張哲維
• Other Authors: 張永佳
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/65453886345131450042

碩士 === 國立交通大學 === 工業工程與管理系所 === 102 === Scheduling of deliveries of large-sized televisions is constrained due to many aspects. For instance, delivery times, delivery vehicles, vehicle’s capacities, delivery routes, limitations with respect to the business hours and personnel abilities. Therefore, delivery of large-sized televisions is a complicated Vehicle Routing Problem (VRP). Whether it is utilizing the company vehicles or outsourcing delivery vehicles, it should be evaluated based on a profit-maximizing perspective rather than the traditional cost minimizing standpoint in order to plan out the scheduling. Therefore, with all the constraints being taken into consideration, scheduling of delivering large sized televisions is a Heterogeneous Fleet Team Orienteering Problem with Time Window (HFTOP-TW). HFTOP-TW is consisted of Team Orienteering Problem (TOP), Heterogeneous Fleet Vehicle Routing Problem (HFVRP), and time window constraint. This research starts by constructing a mathematical model to demonstrate the HFTOP-TW. Due to the fact that this problem is non-polynomial hard (NP-hard), this research applies the Discrete Particle Swarm Optimization (DPSO) for solving such a problem. This research first proposes an algorithm that can calculate initial solutions, then it utilizes greedy route improving strategy to systematically search for better solutions. This research is conducted, tested based on experiments proposed by other researchers in order to prove the effectiveness and efficiency of the proposed method. As per research result, the proposed method has 94% chance of acquiring the best solution. This shows that the proposed method is suitable for solving the scheduling deliveries and services of large-Sized televisions. On top of that, the result also proved the value of the application of the DPSO algorithm and it could be used to maximize profits within reasonable time windows.