01864nas a2200241   4500000000100000000000100001008004100002260001200043653001500055653001900070653001300089653002900102653001600131100004100147700002700188700002300215245008900238856009800327300001000425490000600435520116700441022001401608       2017                            d  c06/201710aAlgorithms10aNeural Network10aHopfield10aArtificial Immune System10aBrute Force1 aMohd Shareduwan Bin Mohd Kasihmuddin1 aMohd Asyraf Bin Mansor1 aSaratha Sathasivam00aRobust Artificial Immune System in the Hopfield network for Maximum k-Satisfiability  uhttp://www.ijimai.org/journal/sites/default/files/files/2016/12/ijimai20174_4_8_pdf_92087.pdf  a63-710 v43 a Artificial Immune System (AIS) algorithm is a novel and vibrant computational paradigm, enthused by the biological immune system. Over the last few years, the artificial immune system has been sprouting to solve numerous computational and combinatorial optimization problems. In this paper, we introduce the restricted MAX-kSAT as a constraint optimization problem that can be solved by a robust computational technique. Hence, we will implement the artificial immune system algorithm incorporated with the Hopfield neural network to solve the restricted MAX-kSAT problem. The proposed paradigm will be compared with the traditional method, Brute force search algorithm integrated with Hopfield neural network. The results demonstrate that the artificial immune system integrated with Hopfield network outperforms the conventional Hopfield network in solving restricted MAX-kSAT. All in all, the result has provided a concrete evidence of the effectiveness of our proposed paradigm to be applied in other constraint optimization problem. The work presented here has many profound implications for future studies to counter the variety of satisfiability problem.  a1989-1660