2017
DOI: 10.1016/j.apenergy.2017.06.015
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Costs and environmental impacts multi-objective heat exchanger networks synthesis using a meta-heuristic approach

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Cited by 28 publications
(9 citation statements)
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“…They found that neither objective alone is sufficient for a balanced process design by applying their framework to CO 2 mitigation in chemical processes and oil and gas plants (105)(106)(107). Pavão et al (108) also chose a derivative-free optimization approach, using a meta-heuristic approach with simulated annealing and particle swarm optimization, to synthesize a heat-exchanger network with minimum cost and environmental impacts.…”
Section: Process Synthesismentioning
confidence: 99%
“…They found that neither objective alone is sufficient for a balanced process design by applying their framework to CO 2 mitigation in chemical processes and oil and gas plants (105)(106)(107). Pavão et al (108) also chose a derivative-free optimization approach, using a meta-heuristic approach with simulated annealing and particle swarm optimization, to synthesize a heat-exchanger network with minimum cost and environmental impacts.…”
Section: Process Synthesismentioning
confidence: 99%
“…Further, Onishi and co-workers developed a larger superstructure with several work-exchange options . The incorporation of environmental impacts to the HEN synthesis problem was assumed in the works of Pavão et al, who handled that objective along with economic aspects via multiobjective optimization (MOO), Mano et al, who approached the problem converting environmental impacts into monetary units, and Onishi et al, who also employed MOO techniques for assessing environmental and economic performances in work and heat integration. Verheyen and Zhang considered uncertain temperatures and flow rates in HEN, presenting a model for multiperiod HEN synthesis based on the SWS of Yee and Grossmann .…”
Section: Introductionmentioning
confidence: 99%
“…In addition, Figures – were optimized using the NNM with stream splits, while Figures and were obtained using the NNM without stream splits. The lowest TACs reported in the literature for cases 1–3 with stream splits are 1,497,325$/yr, 6,712,551$/yr, and 1,462,323$/yr, by Pavão et al, Pavão et al, and Bao et al, respectively, while for cases 3 and 4 without stream splits, the lowest TACs are 1,403,581$/yr and 1,925,783$/yr by Xiao et al, respectively. It can be clearly seen from Table that the TACs obtained using the NNM for cases 1–3 with stream splits are 0.16, 0.34, and 2.97% lower than those reported in the literature, respectively, while in cases 3–4 without stream splits, the obtained TACs are 0.1 and 0.6% lower than those reported in the literature, respectively.…”
Section: Nnm With the Rwce Optimization Mechanismmentioning
confidence: 87%