TABLE OF CONTENTS - The Professional Green Building Council

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Theme B: Creating a livable, healthy and environmentally viable citiesrecovery, fan configuration, filter type and location, motor efficiency, etc. Theoptimal design in light of architectural perspective is based on the ventilationmethod, size and location of diffusers and grilles, the amount of outdoor airflowrate, heat recovery method, etc. In the paper, optimal design from architecturalperspective is of main interest.In general, the optimal design process has two elements [2]:Decision: The designer must make a decision as to which pay-off between thecriteria results in the most desirable design solution;Search: a procedure to search for one or more solutions that reflect the desired payoffbetween the criteria.The relationship between decision and search has three forms [2].A priori preference articulation (decide→search): The most general method wherethe decision maker (DM) predetermines the weight factors according to differentevaluation criteria. For example the initial investment cost is twice as important asthe operation cost.Progressive preference articulation (decide↔search): The DM repeatedly performsdecide and search actions by varying the weight factors until a satisfactory designalternative is found.A posteriori articulation (search→decide): A set of feasible design alternatives isfirst created, and the DM selects an optimal design among them.In this study, (1) initial investment cost, (2) operation cost, (3) percentagedissatisfied (PD) and (4) CO2 concentration are selected as the objective functionelements. Architectural parameters such as ventilation method, size and location ofdiffusers and grilles, the amount of outdoor airflow rate, and heat recovery methodare chosen as design variables. However, the objective function is discontinuous394
Theme B: Creating a livable, healthy and environmentally viable citiesand nonlinear; leading to difficulty to find an optimal solution that minimizes theobjective function elements with a classical optimization method (gradient-basedsearch method). Accordingly, the genetic algorithm (GA) was employed since it isadequate for our optimization problems. For the multi-criteria decision making, the‘A posteriori articulation (search→decide) approach’ was employed using Paretooptimality.2. OPTIMIZATION ALGORITHM2.1 Genetic AlgorithmThe genetic algorithm (GA) solves optimization problems through the evolutionaryprocess. The concept of biological evolution was introduced in [3] and thecomputational algorithm was performed in [4]. It was Schaffer [5] who suggestedthat the GA can be effectively used in solving discontinuous and nonlinearoptimization problems.While the GA is effective in finding the global minima, it is more computationallyextensive than the gradient-based method (Table 1). The GA was employed in thisstudy since it can efficiently solve for nonlinear and nondifferentiable optimizationproblems.Table 1: Comparison of gradient method and GAComparisonGradientGeneticOptimizationAlgorithmNonlinear problem not possible possibleNondifferentiableProblemnot possiblepossiblefinding global minima difficult easycomputing time(speed) fast slow2.2 Pareto OptimalityThe GA optimization is a process of finding global minima from a randomlyselected initial population. The range of feasible solutions is shown in Fig 1 (f1and f2 are objective function elements). The main objective of optimization is not395
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Funding OrganisationCOMMERCE AND EC
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Ms. S.Y. Shum, Anna, Lecturer, Divi
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以绿色思维创新绿色
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ENHANCING SUSTAINABILITY DELIVERABL
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Theme A: Connecting the Pearl River
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精宜之道 ”。所谓 “
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to use suitable technology. Additio
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Theme B: Creating a livable, health
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Page 356 and 357: Theme B: Creating a livable, health
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Average Credit4.03.83.63.43.2Averag
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Theme C: Education and Market Trans
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TABLE OF CONTENTS - The Professional Green Building Council

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