首页|考虑空载损失的非集中式共同配送订单分派及路径优化研究

考虑空载损失的非集中式共同配送订单分派及路径优化研究

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  • 国家科技期刊平台
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物流活动的空载率居高不下源于路径规划不合理及企业间缺少合作,共同配送是降低空载损失的有效模式,但非集中式共同配送下物流企业可能基于被分派的订单选择自身成本最小的配送路径,从而导致共同配送联盟的空载损失变大.本文研究考虑空载损失的非集中式共同配送订单分派及路径优化,首先提出空载损失定义,权衡整个配送过程的成本最小和空载损失最小两个目标,基于非集中式共同配送的特征设计订单分派策略,进而建立订单分派及路径优化模型.设计了基于ε约束法的精确算法、改进的MOPSO(multiple objective particle swarm optimi-zation)算法、多项式时间快速算法进行求解,并结合算例验证算法的有效性.数值分析结果表明,即使物流企业均追求自身成本最小化,提出的订单分派策略也可得到与全局优化相近的结果.
Order Dispatching and Routing for Decentralized Joint Distribution Considering Empty-loading Losses
The high empty-loading rate in logistics activities may result from unreasonable routing and insufficient cooperation among enterprises.Joint distribution is an effective mode to reduce empty-loading losses.However,under the condition of decentralized joint distribution,logistics enterprises may choose the routes with minimum cost based on the assigned orders,resulting in an increase in empty-loading losses of the joint distribution alliance.This study investigates order dispatching and routing for decentralized joint distribution considering empty-loading losses.A definition of empty-loading losses is given firstly.Then,with the trade-off between the objectives of minimizing cost and empty-loading losses in the entire distribution process,an order dispatching strategy is proposed based on the characteristics of decentralized joint distribution mode,and the order dispatching and routing optimization models are developed.A precise algorithm based on epsilon constraint method,an improved MOPSO(Multiple Objective Particle Swarm Optimization)algorithm,and a polynomial-time fast algorithm are developed to solve the problem.The effectiveness of the proposed algorithms is verified based on numerical instances.Analysis results indicate that even if logistics companies pursue cost minimization,the proposed order dispatching strategy can achieve results similar to global optimization.

decentralized joint distributionempty-loading lossesorder dispatchingvehicle routingmulti-objective optimization

张萌、孙璐璐、苏兵、王能民

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西安工业大学 经济管理学院,陕西 西安 710021

西安交通大学 管理学院,陕西 西安 710049

陕西省制造服务业过程挖掘工程研究中心,陕西 西安 710049

非集中式共同配送 空载损失 订单分派 车辆路径 多目标优化

国家自然科学基金重大项目国家自然科学基金重大项目国家自然科学基金国家自然科学基金教育部人文社会科学研究项目陕西省哲学社会科学研究专项陕西省教育厅专项

7219283072192834723012057230122321YJC6301652024QN18123JK0129

2024

10.3969/j.issn.1007-7375.230228

工业工程
广东工业大学

工业工程

CSTPCDCHSSCD
影响因子：0.691
ISSN：1007-7375
年,卷(期)：2024.27(2)
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