Combining Extended Imperialist Competitive Algorithm with a Genetic Algorithm to Solve the Distributed Integration of Process Planning and Scheduling Problem

<table class="table-group" id="tab7"><tr><td><table class="table"><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr class="thead"><td class="align_left">Experiments</td><td class="align_center">GA</td><td class="align_center">EICA</td></tr><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr><td class="align_left">Experiment a</td><td class="align_center">130.23</td><td class="align_center">127.00</td></tr><tr><td class="align_left">Experiment b</td><td class="align_center">144.43</td><td class="align_center">139.43</td></tr><tr><td class="align_left">Experiment c</td><td class="align_center">132.40</td><td class="align_center">125.33</td></tr><tr><td class="align_left">Experiment d</td><td class="align_center">116.63</td><td class="align_center">113.73</td></tr><tr><td class="align_left">Experiment e</td><td class="align_center">114.90</td><td class="align_center">118.57</td></tr><tr class="table-tr"><td colspan="3"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

The average minimum makespan obtained by GA and EICA.

Mathematical Problems in Engineering

tab7

Table 7

Table 7: Combining Extended Imperialist Competitive Algorithm with a Genetic Algorithm to Solve the Distributed Integration of Process Planning and Scheduling Problem 

Table 7 | Combining Extended Imperialist Competitive Algorithm with a Genetic Algorithm to Solve the Distributed Integration of Process Planning and Scheduling Problem 