air quality assessment & management
Reference and User Manual
These combination of sources and control technologies define Optimization Scenarios Within the two-phase optimization approach, the first phase generates a set of alternatives for the subsequent discrete multi-criteria DSS. For the generation of the alternatives (candidate solutions), several alternative strategies can be selected/used, which represents different trade-offs between efficiency/performance (generating large sets of "random" trials fast without feedback as to their "quality") and increasing level of "sophistication", to increase the relative number of feasible and non-dominated solution in this set at the cost of performance, using more complex search strategies and embedded feedback.
is based on a two step random selection procedure:
the first trial on the first source/technology combination yields a starting point; this point has SOME distance from UTOPIA. We can NOW iterate with the application% to get closer to UTOPIA = improvement (we have chosen a point between MIN and MAX; now HALF the larger of the distances to MIN and MAX, evaluate; if it improved, continue in the same direction always halving the remaining distance to MIN or MAX UNTIL the results is WORSE than the previous one, THEN change direction UNTIL we reach some cut-off defined by (a) number of trials or (b) relative improvement [should be scenario configuration parameters]
Heuristic (three types/options)
as above for individual (currently only: boilers) sources; for area (and later LINE sources) INSTEAD of applying the reduction pro-rata to ALL members of the class, apply to INDIVIDUAL MEMBERS 100% until the OVERALL, class specific MAX (as a % of the total baseline emission for that class) has been reached. Apply to the members based on a pre-defined RANKING based on
The changes the weights progressively, based on a continuous analysis of performance/results. As a preparatory step, this requires a preference structure defined: as set of criteria with their optimization direction (min, max, min the deviations from a target), setting of constraints.
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