scholarly journals Minimizing Greenhouse Gas Emissions From Ships Using a Pareto Multi-Objective Optimization Approach

2021 ◽  
Vol 28 (2) ◽  
pp. 96-101
Author(s):  
Zygfryd Domachowski

Abstract To confront climate change, decarbonization strategies must change the global economy. According to statements made as part of the European Green Deal, maritime transport should also become drastically less polluting. As a result, the price of transport must reflect the impact it has on the environment and on health. In such a framework, the purpose of this paper is to suggest a novel method for minimizing emissions from ships, based on so-called Pareto multi-objective optimization. For a given voyage by a ship, the problem is to minimize emissions on the one hand and minimize fuel consumption or passage time on the other. Minimizing emissions is considered as the preferred objective. Therefore, the objective of minimizing fuel consumption or passage time needs to be reformulated as a constraint. Solving such a problem consists of finding most favourable path and speed for the ship and satisfying the optimization criteria. Relatively new systems such as hybrid diesel–electric systems have the potential to offer significant emissions benefits. A hybrid power supply utilizes the maximum efficiency of the direct mechanical drive and the flexibility of a combination of combustion power from the prime mover and stored power from energy storage from an electrical supply, at part load and overload. A new report by the American Bureau of Shipping suggests that maritime transport is likely to meet the International Maritime Organization’s target by 2030, solely by using current technology and operational measures. However, this would not be enough to attain the target of reducing CO2 emissions by 2050 by at least 50% compared to 2008. New technologies and operational methods must be applied.

2020 ◽  
Vol 12 (2) ◽  
pp. 687 ◽  
Author(s):  
Svetla Stoilova

The development of the transport plan must take into account various criteria impacting the transport process. The main objective of the study is to propose an integrated approach to determine the transport plan of passenger trains. The methodology consists of five steps. In the first step, the criteria for optimization of the transport plan were defined. In the second step, variants of the transport plan were formulated. In the third step, the weights of the criteria are determined by applying the step-wise weight assessment ratio analysis method (SWARA) multi-criteria method. The multi-objective optimization was conducted in the fourth step. The following multi-objective optimization approaches were used and compared: weighted sum method (WSM), compromise programming method (CP), and the epsilon–constraint method (EC). The study proposes a modified epsilon–constraint method (MEC) by applying normalization of each objective function according to the maximal value of the solution by individual optimization for each objective function, and hybrid methods: hybrid WSM and EC, hybrid WSM and MEC, hybrid CP and EC, and Hybrid CP and MEC. The impact of the variation of passenger flows on the choice of an optimal transport plan was studied in the fifth step. The Laplace’s criterion, Hurwitz’s criterion, and Savage’s criterion were applied to come to a decision. The approbation of the methodology was demonstrated through the case study of Bulgaria’s railway network. Suitable variant of transport plan is proposed.


2021 ◽  
Vol 9 (5) ◽  
pp. 478
Author(s):  
Hao Chen ◽  
Weikun Li ◽  
Weicheng Cui ◽  
Ping Yang ◽  
Linke Chen

Biomimetic robotic fish systems have attracted huge attention due to the advantages of flexibility and adaptability. They are typically complex systems that involve many disciplines. The design of robotic fish is a multi-objective multidisciplinary design optimization problem. However, the research on the design optimization of robotic fish is rare. In this paper, by combining an efficient multidisciplinary design optimization approach and a novel multi-objective optimization algorithm, a multi-objective multidisciplinary design optimization (MMDO) strategy named IDF-DMOEOA is proposed for the conceptual design of a three-joint robotic fish system. In the proposed IDF-DMOEOA strategy, the individual discipline feasible (IDF) approach is adopted. A novel multi-objective optimization algorithm, disruption-based multi-objective equilibrium optimization algorithm (DMOEOA), is utilized as the optimizer. The proposed MMDO strategy is first applied to the design optimization of the robotic fish system, and the robotic fish system is decomposed into four disciplines: hydrodynamics, propulsion, weight and equilibrium, and energy. The computational fluid dynamics (CFD) method is employed to predict the robotic fish’s hydrodynamics characteristics, and the backpropagation neural network is adopted as the surrogate model to reduce the CFD method’s computational expense. The optimization results indicate that the optimized robotic fish shows better performance than the initial design, proving the proposed IDF-DMOEOA strategy’s effectiveness.


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