Adaptive selection multi-objective optimization method for hybrid flow shop green scheduling under finite variable parameter constraints: case study

2021 ◽  
pp. 1-19
Author(s):  
Zhifeng Liu ◽  
Jun Yan ◽  
Qiang Cheng ◽  
Hongyan Chu ◽  
Jigui Zheng ◽  
...  
Keyword(s):  
Flow Shop ◽  
Variable Parameter ◽  
Optimization Method ◽  
Hybrid Flow Shop ◽  
Multi Objective Optimization ◽  
Adaptive Selection ◽  
Multi Objective ◽  
Parameter Constraints

scholarly journals Comparison of the Economic and Environmental Performance of V2H and Residential Stationary Battery: Development of a Multi-Objective Optimization Method for Homes of EV Owners

2019 ◽  
Vol 10 (4) ◽  
pp. 78
Author(s):  
Ryosuke Kataoka ◽  
Akira Shichi ◽  
Hiroyuki Yamada ◽  
Yumiko Iwafune ◽  
Kazuhiko Ogimoto
Keyword(s):  
Electric Vehicles ◽  
Environmental Performance ◽  
Optimization Method ◽  
Energy Costs ◽  
Multi Objective Optimization ◽  
Environmental Aspects ◽  
Multi Objective ◽  
Investment Cost ◽  
Detached House

The use of batteries of electric vehicles (EVs) for home electricity applications using a bidirectional charger, a process called vehicle-to-home (V2H), is attracting the attention of EV owners as a valuable additional benefit of EVs. To motivate owners to invest in V2H, a quantitative evaluation to compare the performance of EV batteries with that of residential stationary batteries (SBs) is required. In this study, we developed a multi-objective optimization method for the household of EV owners using energy costs including investment and CO2 emissions as indices and compared the performances of V2H and SB. As a case study, a typical detached house in Japan was assumed, and we evaluated the economic and environmental aspects of solar power self-consumption using V2H or SB. The results showed that non-commuting EV owners should invest in V2H if the investment cost of a bidirectional charger is one third of the current cost as compared with inexpensive SB, in 2030. In contrast, our results showed that there were no advantages for commuting EV owners. The results of this study contribute to the rational setting of investment costs to increase the use of V2H by EV owners.

Study on Multi-Objective Optimization of Hybrid Flow Shop Scheduling Problem

2014 ◽  
Vol 1082 ◽  
pp. 529-534
Author(s):  
Zheng Ying Lin ◽  
Wei Zhang
Keyword(s):  
Flow Shop ◽  
Economic Benefits ◽  
Flow Shop Scheduling ◽  
Hybrid Flow Shop ◽  
Scheduling Problem ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Shop Scheduling ◽  
Multi Objective ◽  
Hybrid Flow Shop Scheduling

Due to several mutual conflicting optimized objectives in the hybrid flow shop scheduling problem, its optimized model, including three objectives of make-span, flow-time and tardiness, was firstly set up, instead of the single optimized objective. Furthermore, in order to improve the optimized efficiency and parallelism, after comparing the normal multi-objective optimized methods, an improved NSGA-II algorithm with external archive strategy was proposed. Finally, taking a piston production line as example, its performance was tested. The result showed that the multi-objective optimization of hybrid flow shop scheduling based on improved NSGA-II provided managers with a set of feasible solutions for selection in accordance to their own preference. Therefore the decision could be made more scientific and efficient, and thus brings to the factory more economic benefits.

scholarly journals Problems of a Utopia Point Setting in Transformation of Individual Objective Functions in Multi-Objective Optimization

2019 ◽  
Vol 27 (45) ◽  
pp. 64-71
Author(s):  
Pavel Važan ◽  
Zuzana Červeňanská ◽  
Janette Kotianová ◽  
Jiří Holík
Keyword(s):  
Production Control ◽  
A Priori ◽  
Optimization Method ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Weighted Sum Method ◽  
The Individual ◽  
Utopia Point

Abstract In an optimal processes control, where the considered goals are in general observed as concurrently conflicted, a multi-objective approach fits the best. Commonly used scalarization techniques in multi-objective optimization need a transformation of the individual single-objective functions involved into a scalar multi-criteria objective function. There are many parameters which can influence the optimization results solutions, including an unreachable utopia point value. In this study, the authors compare the multi-objective problem solutions found via two ways of the individual objectives transformation with the respect to setting the utopia point. The methods are used in the area of production control in a case study for a batch production system. To find the solutions, The Weighted Sum Method with a priori articulated preferences under specific constraints as the scalar multi-objective optimization method is applied in simulation optimization.

scholarly journals Efficient multi-objective optimization methods for computationally intensive urban water resources models

2014 ◽  
Vol 17 (1) ◽  
pp. 36-55 ◽  
Author(s):  
Mohammad Mortazavi-Naeini ◽  
George Kuczera ◽  
Lijie Cui
Keyword(s):  
Ant Colony Optimization ◽  
Water Resource ◽  
Optimization Methods ◽  
Optimization Method ◽  
Ant Colony ◽  
Urban Water ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective

Multi-objective optimization methods require many thousands of objective function evaluations. For urban water resource problems such evaluations can be computationally very expensive. The question as to which optimization method is the best choice for a given function evaluations budget in urban water resource problems remains unexplored. The main objective of this paper is to address this question. The second objective is to develop a new optimization algorithm, efficient multi-objective ant colony optimization-I (EMOACO-I), which exploits the good performance of ant colony optimization enhanced using ideas borrowed from evolutionary optimization. Its performance was compared against three established methods (NSGA-II, SMPSO, εMOEA) using two case studies based on the urban water resource systems serving two major Australian cities. The case study problems involved two or three objectives and 10 or 13 decision variables affecting infrastructure investment and system operation. The results show that NSGA-II was the worst performing method. However, none of the remaining methods was unambiguously superior. For example, while EMOACO-I converged more rapidly, its diversity was comparable but not superior to the other methods. Greater differences in performance were found as the number of objectives and case study complexity increased. This suggests that pooling the results from a number of methods could help guard against the vagaries in performance of individual methods.

Sign in / Sign up

Export Citation Format

Share Document