scholarly journals Capacitated Multi-objective Disassembly Scheduling with Fuzzy Processing Time viaAFruit Fly Optimization Algorithm

2021 ◽  
Author(s):  
Gang Yuan ◽  
Yinsheng Yang ◽  
Guangdong Tian ◽  
Amir Mohammad Fathollahi-Fard
Keyword(s):  
Optimization Algorithm ◽  
Cycle Time ◽  
Processing Time ◽  
Programming Model ◽  
Environmental Cost ◽  
Mixed Integer ◽  
Fruit Fly Optimization Algorithm ◽  
Scheduling Problems ◽  
Fruit Fly Optimization ◽  
Multi Objective

Abstract This work proposes a capacitated fuzzy disassembly scheduling model with cycle time and environmental cost, which has broad applications in remanufacturing and many other production systems. Disassembly scheduling is not always given accurately as a time quota in a production system, particularly in the obsolete products remanufacturing process. It is meaningful to study a novel model and algorithm based on uncertainty processing time to solve uncertainty disassembly scheduling problems. Therefore, a mixed-integer mathematical programming model is proposed to minimize the cycle time and environmental cost, whilst a metaheuristic approach based on a fruit fly optimization algorithm is developed to find a fuzzy disassembly scheduling scheme. To estimate the effectiveness of the proposed method, the proposed algorithm is tested with different size cases of products disassembly scheduling. Furthermore, experiments are conducted to compare with other multi-objective optimization algorithms. The computational results demonstrate the proposed algorithm outperforms other algorithms on computational efficiency and applicability performance. Finally, a case study is described to illustrate the proposed method. The main finding of this current work is to provide a new idea to solve the problem of disassembly scheduling in an uncertain environmental practically and efficiently.

scholarly journals Multi-objective optimization model for planning metro-based underground logistics system network: Nanjing case study

2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Xiliang Sun ◽  
Wanjie Hu ◽  
Xiaolong Xue ◽  
Jianjun Dong
Keyword(s):  
Programming Model ◽  
Freight Transport ◽  
Optimization Techniques ◽  
Economic Feasibility ◽  
Environmental Cost ◽  
Mixed Integer ◽  
Logistics System ◽  
Transit System ◽  
Multi Objective ◽  
Good Ability

<p style='text-indent:20px;'>Utilizing rail transit system for collaborative passenger-and-freight transport is a sustainable option to conquer urban congestion. This study proposes effective modeling and optimization techniques for planning a city-wide metro-based underground logistics system (M-ULS) network. Firstly, a novel metro prototype integrating retrofitted underground stations and newly-built capsule pipelines is designed to support automated inbound delivery from urban logistics gateways to in-city destinations. Based on four indicators (i.e. unity of freight flows, regional accessibility, environmental cost-saving, and order priority), an entropy-based fuzzy TOPSIS evaluation model is proposed to select appropriate origin-destination flows for underground freight transport. Then, a mixed integer programming model, with a well-matched solution framework combining multi-objective PSO algorithm and A* algorithm, are developed to optimize the location-allocation-routing (LAR) decisions of M-ULS network. Finally, real-world simulation based on Nanjing metro case is conducted for validation. The best facility configurations and flow assignments of the three-tier M-ULS network are reported in details. Results confirm that the proposed algorithm has good ability in providing high-quality Pareto-optimal LAR decisions. Moreover, the Nanjing M-ULS project shows strong economic feasibility while bringing millions of Yuan of annual external benefit to the society and environment.</p>

scholarly journals A new cellular manufacturing layout: Multi-floor linear cellular manufacturing layout

2020 ◽  
Vol 17 (3) ◽  
pp. 172988142092530
Author(s):  
Yanlin Zhao ◽  
Jiansha Lu ◽  
Wenchao Yi
Keyword(s):  
Optimization Algorithm ◽  
Cellular Manufacturing ◽  
Fruit Fly ◽  
Intelligent Manufacturing ◽  
Population Diversity ◽  
Specific Reference ◽  
Fruit Fly Optimization Algorithm ◽  
Nsga Ii ◽  
Fruit Fly Optimization ◽  
Multi Objective

The article puts forward the new layout methodology of the multi-floor linear cellular manufacturing layout. The proposed equipment layout methodology not just breaks the conventional single-floor linear cellular manufacturing layout but also meets the layout requirements of the intelligent manufacturing workshop for the stereoscopic aisle manufacturing cell. The layout methodology takes into account the least space occupation as well as the shortest total distance of logistics as the objective function, besides considering the limitations that exist between the equipment, different planes, different levels, and so on; also, a mathematical model is put forward. The multi-floor linear cellular manufacturing layout is solved based on the self-adapting multi-objective fruit fly optimization algorithm that refers to an algorithm combining fruit fly optimization algorithm and NSGA-II. Self-adapting multi-objective fruit fly optimization algorithm makes use of the fast nondominated sorting for the multi-target food concentration calculation, together with designing the adaptive olfactory search and visual search, and employing the perturbation operations for flight strategies, aimed at ensuring the population diversity. Simulation cases suggest that self-adapting multi-objective fruit fly optimization algorithm has stronger advantages as compared with multi-objective fruit fly algorithm and elitist non-dominated sorting genetic algorithm (NSGA-II) in the solution of multi-floor linear cellular manufacturing layout problems. The final engineering case application sheds light on the fact that multi-floor linear cellular manufacturing layout saves 57.6% of the area, in addition to 23.7% of space, and 29.2% of the handling distance as compared with single-floor linear cellular manufacturing layout. Accordingly, multi-floor linear cellular manufacturing layout has a specific reference value in the layout of facilities in the intelligent manufacturing plants.

Sign in / Sign up

Export Citation Format

Share Document