An evolutionary trade network game (TNG) is proposed for studying the interplay between evolutionary game dynamics and preferential partner selection in various market contexts with distributed adaptive agents. The modular form of the TNG facilitates experimentation with alternative specifications for trade partner matching, trading, expectation updating, and trade strategy evolution. Experimental results obtained using a C-t-f implementation suggest that the conventional optimal properties used to evaluate agent matching mechanisms in static market contexts may be in an equate measures of optimal from an evolutionary perspective.