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Issue:Multi-objective optimisation in air-conditioning systems: comfort/discomfort definition by IF sets: Difference between revisions
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The problem of multi-objective optimisation of air-conditioning (AC) systems is treated in the paper in the framework of [[intuitionistic fuzzy set theory]]. The nature of the problem is multi-objective one with requirements for minimal costs (generally, life cycle costs; more specifically, energy costs) and maximal occupants' comfort (minimal discomfort). Moreover, its definition by conventional means is bounded to a number of restrictions and assumptions, which are often far from the real-life situations. Attempts have been made to formulate and solve this problem by means of the [[fuzziness|fuzzy]] optimisation. The present paper makes further step by exploring the innovative concept of [[intuitionistic fuzzy sets]] into definition of the trickiest issue: comfort and discomfort definition. The new approach allows to formulate more precisely the problem which compromises energy saving and thermal comfort satisfaction under given constraints. The resulting IF optimisation problem could be solved numerically or, under some assumptions, analytically. An example illustrates the viability of the proposed approach. A solution which significantly (with 35%) improves comfort is found which is more energetically expensive with only 0.6%. This illustrates the possibility to use the approach for trade-off analysis in multi-objective optimisation of AC systems. | The problem of multi-objective optimisation of air-conditioning (AC) systems is treated in the paper in the framework of [[intuitionistic fuzzy set theory]]. The nature of the problem is multi-objective one with requirements for minimal costs (generally, life cycle costs; more specifically, energy costs) and maximal occupants' comfort (minimal discomfort). Moreover, its definition by conventional means is bounded to a number of restrictions and assumptions, which are often far from the real-life situations. Attempts have been made to formulate and solve this problem by means of the [[fuzziness|fuzzy]] optimisation. The present paper makes further step by exploring the innovative concept of [[intuitionistic fuzzy sets]] into definition of the trickiest issue: comfort and discomfort definition. The new approach allows to formulate more precisely the problem which compromises energy saving and thermal comfort satisfaction under given constraints. The resulting IF optimisation problem could be solved numerically or, under some assumptions, analytically. An example illustrates the viability of the proposed approach. A solution which significantly (with 35%) improves comfort is found which is more energetically expensive with only 0.6%. This illustrates the possibility to use the approach for trade-off analysis in multi-objective optimisation of AC systems. | ||
| keywords = [[ | | keywords = [[Intuitionistic fuzzy sets]], IF optimisation, multi-objective optimisation, air-conditioning systems, comfort/discomfort | ||
| references = | | references = | ||
# Angelov P., Optimization in an Intuitionistic Fuzzy Environment, [[Fuzzy Sets and Systems]], 86, 299-306.1997 | # Angelov P., Optimization in an Intuitionistic Fuzzy Environment, [[Fuzzy Sets and Systems]], 86, 299-306.1997 | ||
# Angelov P., [[Issue:Intuitionistic fuzzy optimization|Intuitionistic fuzzy optimization]], [[Notes on Intuitionistic Fuzzy Sets/01/2|"Notes on Intuitionistic Fuzzy Sets", Volume 1, 1995, Number 2]], pages 27-33 | # Angelov P., [[Issue:Intuitionistic fuzzy optimization|Intuitionistic fuzzy optimization]], [[Notes on Intuitionistic Fuzzy Sets/01/2|"Notes on Intuitionistic Fuzzy Sets", Volume 1, 1995, Number 2]], pages 27-33 |
Revision as of 19:08, 18 November 2008
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