en کنترل کیفیت Quality Control پژوهشي Research <em><span style="FONT-FAMILY: "Times New Roman","serif" FONT-SIZE: 11pt mso-ansi-language: EN-US mso-bidi-font-size: 12.0pt mso-fareast-font-family: 'Times New Roman' mso-fareast-language: EN-US mso-bidi-language: FA">The main advantage of heuristic or metaheuristic algorithms compared to exact optimization methods is their ability in handling large-scale instances within a reasonable time, albeit at the expense of losing a guarantee for achieving the optimal solution. Therefore, metaheuristic techniques are appropriate choices for solving NP-hard problems to near optimality. Since the parameters of heuristic and metaheuristic algorithms </span><span style="FONT-FAMILY: "Times New Roman","serif" FONT-SIZE: 11pt mso-ansi-language: EN-US mso-fareast-font-family: 'Times New Roman' mso-fareast-language: EN-US mso-bidi-language: FA">have a great influence on their effectiveness and efficiency, parameter tuning and calibration has gained importance. In this paper a new approach for robust parameter tuning of heuristics and metaheuristics is proposed, which is based on a combination of Design of Experiments (DOE), Signal to Noise (S/N) ratio, </span><span style="FONT-FAMILY: "Times New Roman","serif" FONT-SIZE: 11pt mso-ansi-language: EN-US mso-fareast-font-family: 'Times New Roman' mso-fareast-language: PT mso-bidi-language: FA">Shannon entropy,</span><span style="FONT-FAMILY: "Times New Roman","serif" FONT-SIZE: 11pt mso-ansi-language: EN-US mso-fareast-font-family: 'Times New Roman' mso-fareast-language: EN-US mso-bidi-language: FA"> and VIKOR methods, which not only considers the solution quality or the number of fitness function evaluations, but also aims</span><span style="FONT-FAMILY: "Times New Roman","serif" FONT-SIZE: 11pt mso-ansi-language: EN-US mso-bidi-font-size: 12.0pt mso-fareast-font-family: 'Times New Roman' mso-fareast-language: EN-US mso-bidi-language: FA"> to minimize the running time. In order to evaluate the performance of the suggested approach, a computational analysis has been performed on the Simulated Annealing (SA) and Genetic Algorithms (GA) methods, which have been successfully applied in solving respectively the n-queens and the Uncapacitated Single Allocation Hub Location combinatorial problems. Extensive experimental results showed that by using the presented approach the average number of iterations and the average running time of the SA were respectively improved 12 and 10.2 times compared to the un-tuned SA. Also, the quality of certain solutions was improved in the tuned GA, while the average running time was 2.5 times faster compared to the un-tuned GA</span></em><span style="FONT-FAMILY: "Times New Roman","serif" FONT-SIZE: 10pt mso-ansi-language: EN-US mso-fareast-font-family: 'Times New Roman' mso-fareast-language: EN-US mso-bidi-language: FA">.</span> Parameter Tuning, Design of Experiments, Signal to Noise (S/N) ratio, Shannon Entropy, VIKOR, Simulated Annealing, Genetic Algorithms 143 150 http://ijiepr.iust.ac.ir/browse.php?a_code=A-10-74-1&slc_lang=en&sid=1 Hossein Akbaripour h.akbaripour@modares.ac.ir 180031947532846003172 180031947532846003172 Yes Industrial Engineering Department, Tarbiat Modares University, Tehran, Iran Ellips Masehian masehian@modares.ac.ir 180031947532846003173 180031947532846003173 No Industrial Engineering Department, Tarbiat Modares University, Tehran, Iran