Multi-objective shipment allocation using extreme nondominated sorting genetic algorithm-III (E-NSGA-III)

Conference proceedings article

ผู้เขียน/บรรณาธิการ

กลุ่มสาขาการวิจัยเชิงกลยุทธ์

ไม่พบข้อมูลที่เกี่ยวข้อง

รายละเอียดสำหรับงานพิมพ์

รายชื่อผู้แต่ง: Lavangnananda K., Wangsom P.

ผู้เผยแพร่: Hindawi

ปีที่เผยแพร่ (ค.ศ.): 2019

หน้าแรก: 1500

หน้าสุดท้าย: 1505

จำนวนหน้า: 6

ISBN: 9781728145495

นอก: 0146-9428

eISSN: 1745-4557

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85080925051&doi=10.1109%2fICMLA.2019.00247&partnerID=40&md5=f9679ba14d644cf35bf6756824465010

ภาษา: English-Great Britain (EN-GB)

ดูบนเว็บไซต์ของสำนักพิมพ์

บทคัดย่อ

Dealing with logistical problems are common among companies where delivery of goods are involved. An item to be delivered is commonly known as a shipment and hence efficient shipment allocation is essential for such companies to maintain profits and company competitiveness. This work is concerned with shipment allocation of a large and worldwide delivery company, which has a distribution center in a country where this is still carried manually. Determination of an efficient shipment allocation becomes a multi-objective optimization. Three objectives are identified, these are minimizing number of vehicles used, maximizing vehicle utilization and maximizing operator's route familiarity. Three Multi-Objective Evolution Algorithms (MOEAs) are utilized in this work, these are the commonly known, Nondominated Sorting Genetic Algorithm-III (NSGA-II), Nondominated Sorting Genetic Algorithm-III (NSGA-III) and the recently developed Extreme Nondominated Sorting Genetic Algorithm-III (E-NSGA-III). Hypervolume is used as the metric to measure the quality of solutions. The results from MOEAs reveal superiority over the existing manual solutions. ฉ 2019 IEEE.

คำสำคัญ

E NSGA III, Hypervolume, Logistical problems, MOEA, multiobjective optimization, NSGA II, NSGA III, Shipment allocation