Bi-objective green in-house transportation scheduling and fleet size determination in mixed-model assembly lines with mobile robots. Issue 7 (15th April 2022)

• Record Type: Journal Article
• Authors: Zhou, Binghai; Zhang, Jihua; Fei, Qianran
• Is Part Of: Engineering computations. Volume 39:Issue 7(2022)
• Page Start: 2630
• Page End: 2654
• Publication Date: 2022-04-15
• Subjects: Mixed-model assembly line -- Energy efficiency -- Optimization -- Multi-objective evolutionary algorithm -- In-house transportation; Computer-aided engineering -- Periodicals; Computer graphics -- Periodicals; 620.00285
• DOI: 10.1108/EC-08-2021-0483
• Languages: English
• ISSNs: 0264-4401

Abstract

Abstract : Purpose: Facing the challenge of increasing energy cost and requirement of reducing the emissions, identifying the potential factors of them in the manufacturing factories is an important prerequisite to control energy consumption. This paper aims to present a bi-objective green in-house transportation scheduling and fleet size determination problem (BOGIHTS&FSDP) in automobile assembly line to schedule the material delivery tasks, which jointly take the energy consumption into consideration as well. Design/methodology/approach: This research proposes an optimal method for material handling in automobile assembly line. To solve the problem, several properties and definitions are proposed to solve the model more efficiently. Because of the non-deterministic polynomial-time-hard nature of the proposed problem, a Multi-objective Discrete Differential Evolution Algorithm with Variable Neighborhood Search (VNS-MDDE) is developed to solve the multi-objective problem. Findings: The performances of VNS-MDDE are evaluated in simulation and the results indicate that the proposed algorithm is effective and efficient in solving BOGIHTS&FSDP problem. Originality/value: This study is the first to take advantage of the robot's interactive functions for part supply in automobile assembly lines, which is both the challenge and trend of future intelligent logistics under the pressure of energy and resource. To solve the problem, a VNS-MDDE is developed to solve the multi-objective problem.