A Multiobjective Optimization Approach to a Design Problem of Heat Insulation for Thermal Distribution Piping Network Systems

1983 ◽  
Vol 105 (2) ◽  
pp. 206-213 ◽  
Author(s):  
K. Ito ◽  
S. Akagi ◽  
M. Nishikawa
Keyword(s):  
Optimal Design ◽  
Multiobjective Optimization ◽  
Network Structure ◽  
Design Problem ◽  
Heat Insulation ◽  
Planning System ◽  
Piping System ◽  
Optimization Approach ◽  
Network Systems ◽  
Thermal Distribution

A multiobjective optimization method is applied to a design problem of heat insulation for thermal distribution piping network systems. As the system’s multiple design objectives, the following two mutually conflicting and noncommensurable objective functions are considered simultaneously: (a) minimization of the total amount of heat loss from the whole system, and (b) minimization of the total volume of heat insulating material installed into the whole system. First, for a piping system of fundamental network structure, the set of Pareto optimal solutions is derived for the optimal design problem mentioned above by adopting the weighting method and the generalized reduced gradient algorithm. Second, for the purpose of investigating the same problem for piping systems of more complex network structure, a computer-aided interactive planning system is developed based on decomposition and coordination principles in the theory of hierarchical multilevel systems. Lastly, the validity and the effectiveness of the optimal design method proposed here are ascertained through numerical studies for some typical piping network systems.

A Multi-Objective Optimal Design of Thermal Distribution Systems

1984 ◽  
Vol 106 (2) ◽  
pp. 142-147 ◽  
Author(s):  
K. Ito ◽  
S. Akagi ◽  
M. Ohta
Keyword(s):  
Distribution Systems ◽  
Numerical Study ◽  
Gradient Algorithm ◽  
Planning System ◽  
Piping System ◽  
Optimal Planning ◽  
Objective Functions ◽  
Total Size ◽  
Multi Objective ◽  
Thermal Distribution

A multi-objective nonlinear optimal planning method is proposed to design thermal distribution systems used for district heating. The following three objective functions are considered which are conflicting mutually and noncommensurable with one another; that is, 1) to minimize the total size of piping system, 2) to minimize the pump power, and 3) to minimize the total size of heat exchangers. Adopting the weighting method in multi-objective optimization, the abovementioned multi-objective functions are optimized by using the generalized reduced gradient algorithm. A man-machine interactive optimal planning system is developed to determine the optimally preferred solution from the set of Pareto optimal solutions derived by the method mentioned above. The validity and effectiveness of the design method proposed here are ascertained through a numerical study for a thermal distribution system, and it is certified that much worthwhile information can be obtained by the optimal planning system developed in this study.

An Evolutionary Multi-Objective Optimization Approach to the Topology Optimization of Auxetic Structures

2002 ◽  
Author(s):  
Ashraf O. Nassef
Keyword(s):  
Topology Optimization ◽  
Elastic Modulus ◽  
Finite Elements ◽  
Multiobjective Optimization ◽  
Poisson Ratio ◽  
Optimization Approach ◽  
Multi Objective Optimization ◽  
Finite Elements Analysis ◽  
Multi Objective ◽  
Auxetic Structures

Auxetic structures are ones, which exhibit an in-plane negative Poisson ratio behavior. Such structures can be obtained by specially designed honeycombs or by specially designed composites. The design of such honeycombs and composites has been tackled using a combination of optimization and finite elements analysis. Since, there is a tradeoff between the Poisson ratio of such structures and their elastic modulus, it might not be possible to attain a desired value for both properties simultaneously. The presented work approaches the problem using evolutionary multiobjective optimization to produce several designs rather than one. The algorithm provides the designs that lie on the tradeoff frontier between both properties.

scholarly journals Regularity results for an optimal design problem with a volume constraint

2014 ◽  
Vol 20 (2) ◽  
pp. 460-487 ◽  
Author(s):  
Menita Carozza ◽  
Irene Fonseca ◽  
Antonia Passarelli di Napoli
Keyword(s):  
Optimal Design ◽  
Design Problem ◽  
Volume Constraint ◽  
Optimal Design Problem ◽  
Regularity Results

Design of Electrooptic Modulators Using a Multiobjective Optimization Approach

2008 ◽  
Vol 26 (16) ◽  
pp. 2969-2976 ◽  
Author(s):  
Ademar Muraro ◽  
Angelo Passaro ◽  
Nancy Mieko Abe ◽  
Airam Jonatas Preto ◽  
Stephan Stephany
Keyword(s):  
Multiobjective Optimization ◽  
Optimization Approach ◽  
Electrooptic Modulators

An Integrated Design Optimization Approach for Quantitative and Qualitative Search Space

2003 ◽  
Author(s):  
Victor Oduguwa ◽  
Rajkumar Roy ◽  
Didier Farrugia
Keyword(s):  
Real World ◽  
Design Problem ◽  
Integrated Design ◽  
Search Space ◽  
Optimization Approach ◽  
Design Optimisation ◽  
Solution Approach ◽  
Rod Rolling ◽  
Algorithmic Engineering ◽  
Real World Problems

Most of the algorithmic engineering design optimisation approaches reported in the literature aims to find the best set of solutions within a quantitative (QT) search space of the given problem while ignoring related qualitative (QL) issues. These QL issues can be very important and by ignoring them in the optimisation search, can have expensive consequences especially for real world problems. This paper presents a new integrated design optimisation approach for QT and QL search space. The proposed solution approach is based on design of experiment methods and fuzzy logic principles for building the required QL models, and evolutionary multi-objective optimisation technique for solving the design problem. The proposed technique was applied to a two objectives rod rolling problem. The results obtained demonstrate that the proposed solution approach can be used to solve real world problems taking into account the related QL evaluation of the design problem.

scholarly journals Optimal design of a DC MHD pump by simulated annealing method

2014 ◽  
Vol 11 (2) ◽  
pp. 339-350
Author(s):  
Khadidja Bouali ◽  
Fatima Kadid ◽  
Rachid Abdessemed
Keyword(s):  
Simulated Annealing ◽  
Optimal Design ◽  
Objective Function ◽  
Design Problem ◽  
Design Methodology ◽  
Optimization Problem ◽  
Optimization Procedure ◽  
Simulated Annealing Method ◽  
Direct Interpretation ◽  
Annealing Method

In this paper a design methodology of a magnetohydrodynamic pump is proposed. The methodology is based on direct interpretation of the design problem as an optimization problem. The simulated annealing method is used for an optimal design of a DC MHD pump. The optimization procedure uses an objective function which can be the minimum of the mass. The constraints are both of geometrics and electromagnetic in type. The obtained results are reported.

scholarly journals A MultiObjective Optimization Approach for Integrated Timetabling and Vehicle Scheduling with Uncertainty

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Yindong Shen ◽  
Wenliang Xie ◽  
Jingpeng Li
Keyword(s):  
Multiobjective Optimization ◽  
Planning Process ◽  
Service Level ◽  
Vehicle Scheduling ◽  
Neighborhood Search ◽  
Optimization Approach ◽  
Transit Planning ◽  
Integrated Optimization ◽  
Link Cost ◽  
Integrated Approaches

The timetabling problem (TTP) and vehicle scheduling problem (VSP) are two indispensable problems in public transit planning process. They used to be solved in sequence; hence, optimality of resulting solutions is compromised. To get better results, some integrated approaches emerge to solve the TTP and VSP as an integrated problem. In the existing integrated approaches, the passenger comfort on bus and the uncertainty in the real world are rarely considered. To provide better service for passengers and enhance the robustness of the schedule to be compiled, we study the integrated optimization of TTP and VSP with uncertainty. In this paper, a novel multiobjective optimization approach with the objectives of minimizing the passenger travel cost, the vehicle scheduling cost, and the incompatible trip-link cost is proposed. Meanwhile, a multiobjective hybrid algorithm, which is a combination of the self-adjust genetic algorithm (SGA), large neighborhood search (LNS) algorithm, and Pareto separation operator (PSO), is applied to solve the integrated optimization problem. The experimental results show that the approach outperforms existing approaches in terms of service level and robustness.

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