<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yegul, F.*,</style></author><author><style face="normal" font="default" size="100%">Erenay, F.S.,</style></author><author><style face="normal" font="default" size="100%">Striepe, S.,</style></author><author><style face="normal" font="default" size="100%">Yavuz, M.,</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Improving configuration of complex production lines via simulation-based optimization</style></title><secondary-title><style face="normal" font="default" size="100%">Computers and Industrial Engineering</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2017</style></year></dates><volume><style face="normal" font="default" size="100%">109</style></volume><pages><style face="normal" font="default" size="100%">295-312</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Optimizing the configuration of a complex production line is an NP-hard problem in various machine settings. Solving real-life-size instances of this problem becomes a more common challenge because the current trend of &lt;em&gt;reshoring&lt;/em&gt; induces multi-national firms to transfer manufacturing facilities from workforce-intensive to capital-intensive production environments which usually require re-configuration of the transferred manufacturing systems according to the availability of better machinery in a capital-intensive environment. This paper focuses on the problem of optimizing production line configuration and proposes several simulation-based optimization approaches based on myopic search, ant-colony, simulated annealing, and response-surface methodologies. We investigate the relative performances of these proposed algorithms on a real-life manufacturing system transfer case in automotive industry according to solution quality and computation-time metrics under different parameter scenarios. Thus, our numerical results may guide the decision makers in choosing a suitable solution approach for this problem depending on the problem size and time availability. Our results also illustrate that ant-colony optimization, a methodology not widely applied in simulation-based optimization, provides high-solution quality for this problem when matched-up with a myopic search to find a good initial solution.&lt;/p&gt;</style></abstract></record></records></xml>