Anchored in Irish housing tradition, Bog West: Steve Larkin's rural house resonates with its surroundings and tectonically celebrates domestic life

Full length critical peer review article about House at Bogwest by architect Emmett Scanlon writing for A10. Included visit to the house and an interview with Steve Larkin. Photographs by Alice Clancy. Photographs and plans describing House at Bogwest.

House at Bogwest in County Wexford, Ireland by Steve Larkin Architects

Publication associated with AR House awards 2012 by the Architectural Review. Text includes citation by Jury and based on interview / text with Steve Larkin. Drawings by Steve Larkin and photographs by Alice Clancy.

House in Bogwest, Steve Larkin Architects:Award

2012 AAI Awards Publication by Gandon Editions. Award winning House in Bogwest by Steve Larkin Architects. Includes text by Steve Larkin Architects, Peer Review text by AAI awards 2012 international jury of Architects including Joseph Rykwert, Keith Williams, Noel Brady, Michael McGarry and Ruairí Ó Cuív, Drawings by Steve Larkin and Photographs by Alice Clancy.

House at Bogwest, Wexford, Ireland: Steve Larkin Architect

Critical review of House at Bogwest by Steve Larkin Architects. Text by editorial team, drawings by Steve Larkin and photographs by Alice Clancy.

Distribution-based adaptive bounding genetic algorithm for continuous optimisation problems

A new search-space-updating technique for genetic algorithms is proposed for continuous optimisation problems. Other than gradually reducing the search space during the evolution process with a fixed reduction rate set ‘a priori’, the upper and the lower boundaries for each variable in the objective function are dynamically adjusted based on its distribution statistics. To test the effectiveness, the technique is applied to a number of benchmark optimisation problems in comparison with three other techniques, namely the genetic algorithms with parameter space size adjustment (GAPSSA) technique [A.B. Djurišic, Elite genetic algorithms with adaptive mutations for solving continuous optimization problems – application to modeling of the optical constants of solids, Optics Communications 151 (1998) 147–159], successive zooming genetic algorithm (SZGA) [Y. Kwon, S. Kwon, S. Jin, J. Kim, Convergence enhanced genetic algorithm with successive zooming method for solving continuous optimization problems, Computers and Structures 81 (2003) 1715–1725] and a simple GA. The tests show that for well-posed problems, existing search space updating techniques perform well in terms of convergence speed and solution precision however, for some ill-posed problems these techniques are statistically inferior to a simple GA. All the tests show that the proposed new search space update technique is statistically superior to its counterparts.