Pareto Optimal Solutions for Minimizing Risk and Maximizing Expected Value of Life-Cycle NPV of Production under Nonlinear Constraints

2015 ◽  
Author(s):  
Xin Liu ◽  
Albert C. Reynolds
Keyword(s):  
Life Cycle ◽  
Value Of Life ◽  
Expected Value ◽  
Pareto Optimal ◽  
Nonlinear Constraints ◽  
Pareto Optimal Solutions ◽  
Optimal Solutions

scholarly journals Life-cycle assessment of common water main materials in water distribution networks

2010 ◽  
Vol 13 (3) ◽  
pp. 346-357 ◽  
Author(s):  
L. M. Herstein ◽  
Y. R. Filion
Keyword(s):  
Carbon Monoxide ◽  
Life Cycle Assessment ◽  
Life Cycle ◽  
Water Distribution ◽  
Pareto Optimal ◽  
Pareto Optimal Solutions ◽  
Optimal Solutions ◽  
Metal Mining ◽  
Pvc Pipe ◽  
Pipe Manufacturing

This paper examines the economy-wide environmental impacts linked to the manufacturing of PVC and ductile iron (DI) pipes, steel tanks, and to the generation of electricity for pumping in water distribution network optimization. The non-dominated sorting genetic algorithm (NSGA-II) is used to generate Pareto-optimal solutions of the benchmark ‘Anytown’ network expansion problem. Selected Pareto-optimal solutions of the ‘Anytown’ network are evaluated with an economic input–output life-cycle assessment (EIO-LCA) and 14 environmental measures on air emissions, non-renewable energy use and environmental releases. The major findings suggest that DI and PVC pipe manufacturing and electricity generation activities (for pumping) have higher environmental impacts than steel tank manufacturing and construction activities in the ‘Anytown’ network. The EIO-LCA suggests that DI pipe manufacturing is linked to: (i) carbon monoxide emissions from truck transportation and wholesale trade and (ii) land and underground toxic releases from metal mining activities. PVC pipe manufacturing is linked to: (i) carbon monoxide emissions from truck transportation, (ii) toxic air releases from the plastics material and resin manufacturing sector, (iii) land and underground toxic releases from metal mining and resin manufacturing, and (iv) natural gas use for plastics material and resin manufacturing.

scholarly journals Environmental evaluation of pareto optimal renovation strategies: a multidimensional life-cycle analysis

2020 ◽  
Vol 172 ◽  
pp. 18003
Author(s):  
Yanaika Decorte ◽  
Marijke Steeman ◽  
Nathan Van Den Bossche ◽  
Klaas Calle
Keyword(s):  
Life Cycle ◽  
Net Present Value ◽  
Energy Performance ◽  
Environmental Cost ◽  
Substantial Contribution ◽  
Pareto Optimal ◽  
Life Cycle Approach ◽  
Pareto Optimal Solutions ◽  
Optimal Solutions ◽  
Environmental Aspect

The substantial contribution of buildings in the energy consumption and emissions renders the existing building stock a key element to tackle the climate crisis. Consequently, defining a deliberate decision-making process gains importance. Decisions are currently often based on building codes, budget, and in the best case Pareto optimality of the energy performance and the net present value of the life-cycle cost. The growing attention to sustainability, however, raises questions about the effect of environmental considerations on the outcome of the Pareto optimal solutions. This study quantifies the effect of including the environmental aspect as a third dimension to the current evaluation approach. Therefore, the most appropriate renovation measures are selected using a multidimensional Pareto optimization. The method is applied to a residential high-rise building in Belgium. Firstly, the Pareto front is constituted based on life-cycle costing and life-cycle assessment separately. Subsequently, the respective results are combined into an integrated life cycle approach by enumerating the LCA results as an external cost to the LCC results. The results show that the Pareto optimal solutions from a financial and environmental perspective do not coincide. Although the financial aspect dominates, adding the environmental cost eliminates low-performant financial optima, leading to optimal solutions with a larger insulation thickness.

scholarly journals Optimization Of Multi-Module CrN/CrCN Coatings

2015 ◽  
Vol 60 (2) ◽  
pp. 1037-1043
Author(s):  
Ł. Szparaga ◽  
P. Bartosik ◽  
A. Gilewicz ◽  
J. Ratajski
Keyword(s):  
Optimization Procedure ◽  
Stress And Strain ◽  
Pareto Optimal ◽  
Mutual Distance ◽  
Pareto Optimal Solutions ◽  
Optimal Solutions ◽  
Decision Criteria ◽  
Decision Variables ◽  
42Crmo4 Steel ◽  
The Stability

Abstract In the paper was proposed optimization procedure supporting the prototyping of the geometry of multi-module CrN/CrCN coatings, deposited on substrates from 42CrMo4 steel, in respect of mechanical properties. Adopted decision criteria were the functions of the state of internal stress and strain in the coating and substrate, caused by external mechanical loads. Using developed optimization procedure the set of optimal solutions (Pareto-optimal solutions) of coatings geometry parameters, due to the adopted decision criteria was obtained. For the purposes of analysis of obtained Pareto-optimal solutions, their mutual distance in the space of criteria and decision variables were calculated, which allowed to group solutions in the classes. Also analyzed the number of direct neighbors of Pareto-optimal solutions for the purposes of assessing the stability of solutions.

A DECOMPOSITION-COORDINATION METHOD FOR COMPLEX MULTI-OBJECTIVE SYSTEMS

2009 ◽  
Vol 26 (06) ◽  
pp. 735-757 ◽  
Author(s):  
F. MIGUEL ◽  
T. GÓMEZ ◽  
M. LUQUE ◽  
F. RUIZ ◽  
R. CABALLERO
Keyword(s):  
Information Exchange ◽  
Exchange Process ◽  
Efficient Solutions ◽  
Pareto Optimal ◽  
Relative Importance ◽  
Pareto Optimal Solutions ◽  
Optimal Solutions ◽  
Conflicting Objectives ◽  
Upper Level ◽  
Problem Instances

The generation of Pareto optimal solutions for complex systems with multiple conflicting objectives can be easier if the problem can be decomposed and solved as a set of smaller coordinated subproblems. In this paper, a new decomposition-coordination method is proposed, where the global problem is partitioned into subsystems on the basis of the connection structure of the mathematical model, assigning a relative importance to each of them. In order to obtain Pareto optimal solutions for the global system, the aforementioned subproblems are coordinated taking into account their relative importance. The scheme that has been developed is an iterative one, and the global efficient solutions are found through a continuous information exchange process between the coordination level (upper level) and the subsystem level (lower level). Computational experiments on several randomly generated problem instances show that the suggested algorithm produces efficient solutions within reasonable computational times.

Multiobjective optimization of the flaxseed mucilage extraction process using normal-boundary intersection approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mariana Souza Rocha ◽  
Luiz Célio Souza Rocha ◽  
Marcia Barreto da Silva Feijó ◽  
Paula Luiza Limongi dos Santos Marotta ◽  
Samanta Cardozo Mourão
Keyword(s):  
Multiobjective Optimization ◽  
Optimization Method ◽  
Extraction Process ◽  
Pareto Optimal ◽  
Pareto Optimal Solutions ◽  
Optimal Solutions ◽  
Fiber Concentration ◽  
Trade Off ◽  
Content Type ◽  
Normal Boundary

PurposeThe mucilage of the Linum usitatissimum L. seed (Linseed) is one of the natural mucilages that presents a great potential to provide a food hydrocolloid with potential applications in both food and pharmaceutical industries. To increase the yield and quality of linseed oil during its production process, it is necessary to previously extract its polysaccharides. Because of this, flax mucilage production can be made viable as a byproduct of oil extraction process, which is already a product of high commercial value consolidated in the market. Thus, the purpose of this work is to optimize the mucilage extraction process of L. usitatissimum L. using the normal-boundary intersection (NBI) multiobjective optimization method.Design/methodology/approachCurrently, the variables of the process of polysaccharide extraction from different sources are optimized using the response surface methodology. However, when the optimal points of the responses are conflicting it is necessary to study the best conditions to achieve a balance between these conflicting objectives (trade-offs) and to explore the available options it is necessary to formulate an optimization problem with multiple objectives. The multiobjective optimization method used in this work was the NBI developed to find uniformly distributed and continuous Pareto optimal solutions for a nonlinear multiobjective problem.FindingsThe optimum extraction point to obtain the maximum fiber concentration in the extracted material was pH 3.81, temperature of 46°C, time of 13.46 h. The maximum extraction yield of flaxseed was pH 6.45, temperature of 65°C, time of 14.41 h. This result confirms the trade-off relationship between the objectives. NBI approach was able to find uniformly distributed Pareto optimal solutions, which allows to analyze the behavior of the trade-off relationship. Thus, the decision-maker can set extraction conditions to achieve desired characteristics in mucilage.Originality/valueThe novelty of this paper is to confirm the existence of a trade-off relationship between the productivity parameter (yield) and the quality parameter (fiber concentration in the extracted material) during the flaxseed mucilage extraction process. The NBI approach was able to find uniformly distributed Pareto optimal solutions, which allows us to analyze the behavior of the trade-off relationship. This allows the decision-making to the extraction conditions according to the desired characteristics of the final product, thus being able to direct the extraction for the best applicability of the mucilage.

scholarly journals Two-Step Many-Objective Optimal Power Flow Based on Knee Point-Driven Evolutionary Algorithm

Processes ◽  
2018 ◽  
Vol 6 (12) ◽  
pp. 250 ◽  
Author(s):  
Yahui Li ◽  
Yang Li
Keyword(s):  
Decision Analysis ◽  
Evolutionary Algorithm ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Decision Makers ◽  
Pareto Optimal ◽  
Pareto Optimal Solutions ◽  
Optimal Solutions ◽  
Optimal Power ◽  
Knee Point

To coordinate the economy, security and environment protection in the power system operation, a two-step many-objective optimal power flow (MaOPF) solution method is proposed. In step 1, it is the first time that knee point-driven evolutionary algorithm (KnEA) is introduced to address the MaOPF problem, and thereby the Pareto-optimal solutions can be obtained. In step 2, an integrated decision analysis technique is utilized to provide decision makers with decision supports by combining fuzzy c-means (FCM) clustering and grey relational projection (GRP) method together. In this way, the best compromise solutions (BCSs) that represent decision makers’ different, even conflicting, preferences can be automatically determined from the set of Pareto-optimal solutions. The primary contribution of the proposal is the innovative application of many-objective optimization together with decision analysis for addressing MaOPF problems. Through examining the two-step method via the IEEE 118-bus system and the real-world Hebei provincial power system, it is verified that our approach is suitable for addressing the MaOPF problem of power systems.

Solving Environmental/Economic Dispatch Problem

2010 ◽  
pp. 123-145
Author(s):  
M.A. Abido
Keyword(s):  
Environmental Economic ◽  
Economic Dispatch ◽  
Test System ◽  
Standard Test ◽  
Pareto Optimal ◽  
Pareto Optimal Solutions ◽  
Optimal Solutions ◽  
Swarm Optimization ◽  
Nondominated Solutions ◽  
Multiobjective Particle Swarm Optimization

Multiobjective particle swarm optimization (MOPSO) technique for environmental/economic dispatch (EED) problem is proposed and presented in this work. The proposed MOPSO technique evolves a multiobjective version of PSO by proposing redefinition of global best and local best individuals in multiobjective optimization domain. The proposed MOPSO technique has been implemented to solve the EED problem with competing and non-commensurable cost and emission objectives. Several optimization runs of the proposed approach have been carried out on a standard test system. The results demonstrate the capabilities of the proposed MOPSO technique to generate a set of well-distributed Pareto-optimal solutions in one single run. The comparison with the different reported techniques demonstrates the superiority of the proposed MOPSO in terms of the diversity of the Pareto optimal solutions obtained. In addition, a quality measure to Pareto optimal solutions has been implemented where the results confirm the potential of the proposed MOPSO technique to solve the multiobjective EED problem and produce high quality nondominated solutions.

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