A novel optimized cyclic part feeding system with line-integrated supermarkets

Zhang

Fei

2022

Self Cite

PurposeFacing 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/approachThis 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.FindingsThe 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/valueThis 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.

Section: Problem Formulationmentioning

confidence: 99%

“…A set of instances are generated based on a set of benchmark instances of the automobile assembly line part supply problem, available in the literature (Boysen and Emde, 2014; Zhou and Xu, 2018). The part demand of each workstation is generated randomly from uniform distribution ⌊rnduni(0,4)⌋.…”

Section: Computational Studymentioning

confidence: 99%

Bi-objective green in-house transportation scheduling and fleet size determination in mixed-model assembly lines with mobile robots

Zhang

Fei

2022

Self Cite

“…For more recent studies, please refer to Boysen et al., 16 Emde and Gendreau, 17 and Zhou et al. 18,19 These works present mathematical formulations and algorithm designs in different problem settings, which are instructive to the current research.…”

Section: Literature Surveymentioning

confidence: 99%

Scheduling just-in-time part replenishment of the automobile assembly line with unrelated parallel machines

Proceedings of the Institution of Mechanical Engineers, Part C:

Peng

2019

Self Cite

With increasing product customization, just-in-time part replenishment has become a significant scheduling problem in the automobile assembly system. This paper investigates a new unrelated parallel machine scheduling problem of an assembly line, where machines are employed to deliver material boxes from an in-house warehouse to workstations. The schedule is to appropriately specify the assignment and sequence of material boxes on each machine for minimizing line-side inventories under no stock-out constraints. By taking advantages of domain properties, an exact algorithm is developed to cope up with small-scale instances. In terms of real-world scale instances, a hybrid teaching–learning-based optimization metaheuristic is established by integrating teaching–learning-based optimization with a beam search technique. Experimental results indicate that the scheduling algorithms are effective and efficient in solving the proposed unrelated parallel machine scheduling.

“…Nonetheless, Material feeding activities are usually considered as non-value-added processes, which means that they cannot create actual benefits or values for enterprises (Zhou & Xu, 2019). Therefore, it is of theoretical meaning and application value to study the material feeding scheduling problems with cost consideration.…”

Section: Introductionmentioning

confidence: 99%

A shuffled frog leaping-based hyper heuristic algorithm for material feeding scheduling optimization in an automatic monorail shuttle system

Zhao

2023

Preprint

Self Cite

In recent years, mixed-model assembly lines (MMALs) have been widely adopted by the automotive enterprises to face the requirements of mass customization. Meanwhile, the diversified components of various end products are placing the material feeding processes at great challenges. Under this circumstance, to raise the material feeding efficiency, this paper proposes an automatic monorail shuttle system (AMSS) based on line-integrated supermarkets applied to the MMALs by introducing the load-exchangeable shuttles and crossovers. Considering the importance of cost-control in manufacturing enterprises, we establish a mathematical model with the objective to minimize the total costs of the material feeding system, which includes the installation costs of crossovers and the input and operation costs of load-exchangeable shuttles. Then, due to the NP-hard nature of the proposed problem, a shuffled frog leaping-based hyper heuristic (SBHH) algorithm is developed to determine the allocation and scheduling of the shuttles and crossovers, which adopts the shuffled frog leaping algorithm (SFLA) as the high-level heuristic to select the low-level heuristics. To improve the performance of the algorithm, the concept of ‘dynamic decision unit’ is presented to raise the solution accuracy and the convergence speed. Finally, the simulation results verified the superiority of the proposed SBHH algorithm both in solution quality and convergence speed by comparing with other optimization algorithm in the existing literature.