This paper presents a new approach to selection of a set of recorded earthquake ground motions that in combination match a given site-specific design spectrum with minimum alteration. The scaling factors applied to selected ground motions are scalar values within the range specified by the user. As a result, the phase and shape of the response spectra of earthquake ground motions are not tampered with. Contrary to the prevailing scaling methods where a preset number of earthquake records (usually between a single component to seven pairs) are selected first and scaled to match the design spectrum next, the proposed method is capable of searching a set consisting of thousands of earthquake records and recommending a desired subset of records that match the target design spectrum. This task is achieved by using a genetic algorithm (GA), which treats the union of 7 records and corresponding scaling factors as a single ''individual.'' The first generation of individuals may include a population of, for example, 200 records. Then, through processes that mimic mating, natural selection, and mutation, new generations of individuals are produced and the process continues until an optimum individual (seven pairs and scaling factors) is obtained. The procedure is fast and reliable and results in records that match the target spectrum with minimal tampering and the least mean square of deviation from the target spectrum.

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Significant progress has been made in the preceding two decades in the area of seismic engineering. Design codes are very quickly migrating from prescriptive procedures intended to preserve life safety to reliability-based design with less prescription intended to quantify risk associated with designs. Therefore, all stakeholders are given the opportunity to speak a common language ͑probability and risk͒ leading to structural designs that not only reliably preserve life safety after rare ground motions, but minimize damage after more frequent ground motions and thereby minimize life-cycle costs. Probabilistic performance-based design is in between traditional prescriptive design methods and full reliability-based design methodologies. The present paper provides an overview of a state-of-the-art modelcode performance-based design methodology and casts this design procedure into multiple-objective optimization problems for singlestory and multistory structural steel frameworks with fully and partially restrained connections. A methodology for applying an evolutionary ͑genetic͒ algorithm with radial fitness and balanced fitness functions is discussed in detail. A companion paper provides applications of the automated design algorithm to single-story frames and multistory frames with a variety of connection characteristics and beam-to-column moment capacity ratios.