PaletteViz with Star-coordinates: An Improved Method for High-dimensional Pareto-optimal Front Visualization and Decision-making

2020 ◽  
Author(s):  
AKM Khaled Ahsan Talukder ◽  
Kalyanmoy Deb
Keyword(s):  
Decision Making ◽  
High Dimensional ◽  
Pareto Optimal ◽  
Improved Method ◽  
Pareto Optimal Front

scholarly journals An Improved SPEA2 Algorithm with Local Search for Multi-Objective Investment Decision-Making

2019 ◽  
Vol 9 (8) ◽  
pp. 1675 ◽  
Author(s):  
Xi Liu ◽  
Dan Zhang
Keyword(s):  
Decision Making ◽  
Local Search ◽  
Investment Decision ◽  
Global Search ◽  
Pareto Optimal ◽  
Multi Objective Optimization ◽  
Improved Method ◽  
Optimal Boundary ◽  
Multi Objective ◽  
Investment Decision Making

Enterprise investment decision-making should not only consider investment profits, but also investment risks, which is a complex nonlinear multi-objective optimization problem. However, traditional investment decisions often only consider profit as a goal, resulting in an incorrect decision. Facing the high complexity of investment decision-making space, traditional multi-objective optimization methods pay too much attention to global search ability because of pursuing convergence speed and avoiding falling into local optimum, while local search ability is insufficient, which makes it difficult to converge to the Pareto optimal boundary. To solve this problem, an improved SPEA2 algorithm is proposed to optimize the multi-objective decision-making of investment. In the improved method, an external archive set is set up separately for local search after genetic operation, which guarantees the global search ability and also has strong local search ability. At the same time, the new crossover operator and individual update strategy are used to further improve the convergence ability of the algorithm while maintaining a strong diversity of the population. The experimental results show that the improved method can converge to the Pareto optimal boundary and improve the convergence speed, which can effectively realize the multi-objective decision-making of investment.

scholarly journals Integration of Operability Framework and Pareto Optimal Front to Calculate Optimal Condition of Ethane Cracking Process

2020 ◽  
pp. 105-113
Author(s):  
M. Farsi
Keyword(s):  
Pareto Front ◽  
Optimal Solution ◽  
Optimization Procedure ◽  
Operating Conditions ◽  
Base Case ◽  
Pareto Optimal ◽  
Multi Objective Optimization ◽  
Pareto Optimal Front ◽  
Multi Objective ◽  
Cracking Process

The main aim of this research is to present an optimization procedure based on the integration of operability framework and multi-objective optimization concepts to find the single optimal solution of processes. In this regard, the Desired Pareto Index is defined as the ratio of desired Pareto front to the Pareto optimal front as a quantitative criterion to analyze the performance of chemical processes. The Desired Pareto Front is defined as a part of the Pareto front that all outputs are improved compared to the conventional operating condition. To prove the efficiency of proposed optimization method, the operating conditions of ethane cracking process is optimized as a base case. The ethylene and methane production rates are selected as the objectives in the formulated multi-objective optimization problem. Based on the simulation results, applying the obtained operating conditions by the proposed optimization procedure on the ethane cracking process improve ethylene production by about 3% compared to the conventional condition.  

Optimizing agricultural production with socioeconomic considerations: A case study from Palestine

2020 ◽  
Vol 8 (2) ◽  
pp. 54-89
Author(s):  
Fathi M. Anayah
Keyword(s):  
Decision Making ◽  
Agricultural Production ◽  
Multiple Criteria Decision Making ◽  
Irrigated Agriculture ◽  
Multiple Objective ◽  
Pareto Optimal ◽  
Net Benefit ◽  
Weighted Goal Programming ◽  
Socioeconomic Considerations

Agriculture is not only the main source of income to most Palestinian families; it is also the link to connect them to their valuable land and water resources. Farmers seek assistance from agronomists and decision makers to cultivate the proper products. In this study, the best selection of agricultural crops is addressed in the multiple-objective context. The study deals with three conflicting objective functions: net benefit, agricultural production, and labor employment. Four-stage procedure is adopted combining multiple-objective optimization, simple valuation methods, cluster analysis, and multiple criteria decision making (MCDM) methods. Pareto optimal curves are used to evaluate the marginal prices of both land area and labor day. The theories of utility and benefit cost are applied to rank the non-dominant alternatives. Two MCDM methods, namely weighted goal programming and step methods, are employed in the evaluation. The above methodology is applied to the case study of Qalqilya District in which irrigated agriculture under semi-arid conditions prevails. The results show that Pareto optimal is a powerful tool to determine the marginal price of non-monetary commodities. It is also found that the average annual net benefit, agricultural production, and labor employment for the cultivated area are $941,423, 3,288 tons, and 14,671 days, respectively, in the best compromise plan. The inclusion of socioeconomic considerations in decision making on agricultural systems is crucial for their sustainable development.

Pareto optimal directional drilling advisory for improved real-time decision making

2021 ◽  
pp. 110031
Author(s):  
John D'Angelo ◽  
Mohamed Shafik Khaled ◽  
Pradeepkumar Ashok ◽  
Eric van Oort
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Pareto Optimal ◽  
Directional Drilling

Optimizing agricultural production with socioeconomic considerations: A case study from Palestine

2020 ◽  
Vol 8 (2) ◽  
pp. 54-89
Author(s):  
Fathi M. Anayah
Keyword(s):  
Decision Making ◽  
Agricultural Production ◽  
Multiple Criteria Decision Making ◽  
Irrigated Agriculture ◽  
Multiple Objective ◽  
Pareto Optimal ◽  
Net Benefit ◽  
Weighted Goal Programming ◽  
Socioeconomic Considerations

Agriculture is not only the main source of income to most Palestinian families; it is also the link to connect them to their valuable land and water resources. Farmers seek assistance from agronomists and decision makers to cultivate the proper products. In this study, the best selection of agricultural crops is addressed in the multiple-objective context. The study deals with three conflicting objective functions: net benefit, agricultural production, and labor employment. Four-stage procedure is adopted combining multiple-objective optimization, simple valuation methods, cluster analysis, and multiple criteria decision making (MCDM) methods. Pareto optimal curves are used to evaluate the marginal prices of both land area and labor day. The theories of utility and benefit cost are applied to rank the non-dominant alternatives. Two MCDM methods, namely weighted goal programming and step methods, are employed in the evaluation. The above methodology is applied to the case study of Qalqilya District in which irrigated agriculture under semi-arid conditions prevails. The results show that Pareto optimal is a powerful tool to determine the marginal price of non-monetary commodities. It is also found that the average annual net benefit, agricultural production, and labor employment for the cultivated area are $941,423, 3,288 tons, and 14,671 days, respectively, in the best compromise plan. The inclusion of socioeconomic considerations in decision making on agricultural systems is crucial for their sustainable development.

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