A simultaneous approach for the synthesis of multiperiod heat exchanger network using particle swarm optimization

2017 ◽  
Vol 96 (5) ◽  
pp. 1142-1155 ◽  
Author(s):  
Gercio P. Silva ◽  
Camila B. Miranda ◽  
Esdras P. Carvalho ◽  
Mauro A. S. S. Ravagnani
Keyword(s):  
Particle Swarm Optimization ◽  
Heat Exchanger ◽  
Particle Swarm ◽  
Heat Exchanger Network ◽  
Swarm Optimization ◽  
Simultaneous Approach

Flexible Synthesis of Heat Exchanger Network with Particle Swarm Optimization Algorithm

2011 ◽  
Vol 214 ◽  
pp. 569-572 ◽  
Author(s):  
Xio Ling Zhang ◽  
Hong Chao Yin ◽  
Zhao Yi Huo
Keyword(s):  
Particle Swarm Optimization ◽  
Heat Exchanger ◽  
Operating Cost ◽  
Particle Swarm ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Optimization Approach ◽  
Nonlinear Program ◽  
Heat Exchanger Network ◽  
Swarm Optimization

In this paper, the flexible synthesis problem for heat exchanger network(HEN) is formulated to a mixed integer nonlinear program(MINLP) model. The objection function of the model consists of two components: First, a candidate HEN structure has to satisfy flexible criterion during input span. Second, a minimized annual cost consisting of investment cost and operating cost is investigated. The solution strategy based on particle swarm optimization(PSO) algorithm is proposed to obtain the optimal solution of the presented model. Finally, a four streams example is investigated to show the advantage of the whole proposed optimization approach.

Optimal Heat Exchanger Network Synthesis via Particle Swarm Optimization

2011 ◽  
Vol 148-149 ◽  
pp. 1468-1472
Author(s):  
Ping Wang ◽  
Jun Liang Xu ◽  
Tao Lu
Keyword(s):  
Particle Swarm Optimization ◽  
Heat Exchanger ◽  
Particle Swarm ◽  
Network Synthesis ◽  
Heat Exchanger Network ◽  
Swarm Optimization ◽  
Modified Particle Swarm Optimization ◽  
Solution Accuracy ◽  
Operation Cost ◽  
Heat Exchanger Network Synthesis

On the basis of superstructure of heat exchanger network (HEN), we established a particle swarm optimization (PSO) model of HEN with no splits, with the target of minimizing investment and operation cost. A typical HEN was solved via a modified particle swarm optimization (PSO). Through comparative of the optimization result, we could know that this method could reach better solution accuracy.

Solving Large-Scale Heat Exchanger Network Synthesis Problems Using Particle Swarm Optimization

2011 ◽  
Vol 148-149 ◽  
pp. 636-640 ◽  
Author(s):  
Zhao Yi Huo ◽  
Liang Zhao ◽  
Hong Chao Yin
Keyword(s):  
Particle Swarm Optimization ◽  
Heat Exchanger ◽  
Large Scale ◽  
Particle Swarm ◽  
Network Synthesis ◽  
Heat Exchanger Network ◽  
Swarm Optimization ◽  
Optimal Network ◽  
Simultaneous Synthesis ◽  
Heat Exchanger Network Synthesis

Heat exchanger network synthesis has been one of the most popular subjects in process design over the last 50 years. Various studies and optimization techniques have been proposed for designing optimal network with minimum total annual cost. Simultaneous synthesis approach via mathematical programming aims to find the optimal network without decomposition, which has been paid more attentions on the research recently. However, these methods might be not solvable or inefficient for large-scale problems. This paper makes an attempt to construct simultaneous synthesis model with split streams and to develop an efficient optimization framework based on particle swarm optimization for large-scale heat exchanger network synthesis problems. One example including 20 process streams is solved to give an illustration of the method.

Optimal heat exchanger network synthesis using particle swarm optimization

2009 ◽  
Vol 11 (3) ◽  
pp. 459-470 ◽  
Author(s):  
Aline P. Silva ◽  
Mauro A. S. S. Ravagnani ◽  
Evaristo C. Biscaia ◽  
Jose A. Caballero
Keyword(s):  
Particle Swarm Optimization ◽  
Heat Exchanger ◽  
Particle Swarm ◽  
Network Synthesis ◽  
Heat Exchanger Network ◽  
Swarm Optimization ◽  
Optimal Heat ◽  
Heat Exchanger Network Synthesis

Optimization of Shell and Tube Heat Exchanger Using Alpha Tuning Elephant Herding Optimization (EHO) Technique

2021 ◽  
Vol 52 ◽  
pp. 92-101
Author(s):  
Jiten Makadia ◽  
C.D. Sankhavara
Keyword(s):  
Particle Swarm Optimization ◽  
Heat Exchanger ◽  
Optimization Problems ◽  
Cost Optimization ◽  
Real Life ◽  
Particle Swarm ◽  
Benchmark Problems ◽  
Swarm Optimization ◽  
Tube Heat Exchanger ◽  
Shell And Tube

Swarm Intelligence algorithms like PSO (Particle Swarm Optimization), ACO (Ant Colony Optimization), ABC (Artificial Bee Colony), Glow-worm swarm Optimization, etc. have been utilized by researchers for solving optimization problems. This work presents the application of a novel modified EHO (Elephant Herding Optimization) for cost optimization of shell and tube heat exchanger. A comparison of the results obtained by EHO in two benchmark problems shows that it is superior to those obtained with genetic algorithm and particle swarm optimization. The overall cost reduction is 13.3 % and 9.68% for both the benchmark problem compared to PSO. Results indicate that EHO can be effectively utilized for solving real-life optimization problems.

Hybrid Particle Swarm Optimization and Ant Colony Optimization Technique for the Optimal Design of Shell and Tube Heat Exchangers

2015 ◽  
Vol 10 (2) ◽  
pp. 81-96 ◽  
Author(s):  
Sandip K. Lahiri ◽  
Nadeem Muhammed Khalfe
Keyword(s):  
Particle Swarm Optimization ◽  
Heat Exchanger ◽  
Heat Exchangers ◽  
Optimization Technique ◽  
Particle Swarm ◽  
Ant Colony ◽  
Swarm Optimization ◽  
Hybrid Particle Swarm Optimization ◽  
Shell And Tube ◽  
Operational Constraints

Abstract Owing to the wide utilization of shell and tube heat exchangers (STHEs) in industrial processes, their cost minimization is an important target for both designers and users. Traditional design approaches are based on iterative procedures which gradually change the design and geometric parameters until satisfying a given heat duty and set of geometric and operational constraints. Although well proven, this kind of approach is time-consuming and may not lead to cost-effective design. The present study explores the use of non-traditional optimization technique called hybrid particle swarm optimization (PSO) and ant colony optimization (ACO), for design optimization of STHEs from economic point of view. The PSO applies for global optimization and ant colony approach is employed to update positions of particles to attain rapidly the feasible solution space. ACO works as a local search, wherein ants apply pheromone-guided mechanism to update the positions found by the particles in the earlier stage. The optimization procedure involves the selection of the major geometric parameters such as tube diameters, tube length, baffle spacing, number of tube passes, tube layout, type of head, baffle cut, etc. and minimization of total annual cost is considered as design target. The methodology takes into account the geometric and operational constraints typically recommended by design codes. Three different case studies are presented to demonstrate the effectiveness and accuracy of proposed algorithm. The examples analyzed show that the hybrid PSO and ACO algorithm provides a valuable tool for optimal design of heat exchanger. The hybrid PSO and ACO approach is able to reduce the total cost of heat exchanger as compare to cost obtained by previously reported genetic algorithm (GA) approach. The result comparisons with particle swarm optimizer and other optimization algorithms (GA) demonstrate the effectiveness of the presented method.

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