A Two-Stage Green Supply Chain Network with a Carbon Emission Price by a Multi-objective Interior Search Algorithm

Abstract

<span class="shorttext"><span style="font-size: 8.0pt; font-family: 'Times New Roman',serif;">This paper presented a new two-stage green supply chain network, in which includes two innovations.</span></span><span style="font-size: 8.0pt; font-family: 'Times New Roman',serif;"> Firstly, it presents a new multi-objective model for a two-stage green supply chain problem that considers the amount of shortage in the network, reworking, and carbon-trading cost produced in the green supply chain. Secondly, </span><span style="font-size: 8.0pt; font-family: 'Times New Roman',serif; mso-ansi-language: EN; mso-bidi-language: AR-SA;" lang="EN">because of the complexity of this model</span><span style="font-size: 8.0pt; font-family: 'Times New Roman',serif;">, it uses<span class="shorttext"> a new multi-objective </span>interior search algorithm (MOISA) to solve the presented model. </span><span style="font-size: 8.0pt; font-family: 'Times New Roman',serif; mso-ansi-language: EN; mso-bidi-language: AR-SA;" lang="EN">The obtained results of the proposed algorithm were compared with the results of</span><span style="font-size: 8.0pt; font-family: 'Times New Roman',serif;"> other multi-objective meta-heuristics, namely MOPSO, SPEA2, and NSGA-II. The outcomes demonstrate that the proposed MOISA gives better Pareto solutions </span><span style="font-size: 8.0pt; font-family: 'Times New Roman',serif; mso-ansi-language: EN; mso-bidi-language: AR-SA;" lang="EN">and indicates the superiority of the proposed algorithm in most cases.</span><br /> <span class="shorttext"><span style="font-size: 8.0pt; font-family: 'Times New Roman',serif;">This paper presented a new two-stage green supply chain network, in which includes two innovations.</span></span><span style="font-size: 8.0pt; font-family: 'Times New Roman',serif;"> Firstly, it presents a new multi-objective model for a two-stage green supply chain problem that considers the amount of shortage in the network, reworking, and carbon-trading cost produced in the green supply chain. Secondly, </span><span style="font-size: 8.0pt; font-family: 'Times New Roman',serif; mso-ansi-language: EN; mso-bidi-language: AR-SA;" lang="EN">because of the complexity of this model</span><span style="font-size: 8.0pt; font-family: 'Times New Roman',serif;">, it uses<span class="shorttext"> a new multi-objective </span>interior search algorithm (MOISA) to solve the presented model. </span><span style="font-size: 8.0pt; font-family: 'Times New Roman',serif; mso-ansi-language: EN; mso-bidi-language: AR-SA;" lang="EN">The obtained results of the proposed algorithm were compared with the results of</span><span style="font-size: 8.0pt; font-family: 'Times New Roman',serif;"> other multi-objective meta-heuristics, namely MOPSO, SPEA2, and NSGA-II. The outcomes demonstrate that the proposed MOISA gives better Pareto solutions </span><span style="font-size: 8.0pt; font-family: 'Times New Roman',serif; mso-ansi-language: EN; mso-bidi-language: AR-SA;" lang="EN">and indicates the superiority of the proposed algorithm in most cases.</span>