An efficient matheuristic algorithm for bi-objective sustainable closed-loop supply chain networks

Abstract This paper develops an optimization model for a sustainable closed-loop supply chain network with two conflicting objectives, namely, the minimization of total logistic costs and amount carbon emissions. The first objective relates to financial benefits, whereas second represents wider goal guaranteeing cleaner air hence greener healthier planet. problem is modelled as mixed integer linear programming based-model. aim determine location distribution centres recycling centres, their respective numbers type vehicles assigned each facility. Vehicle consideration, not commonly used in literature, adds another dimension this practical challenging problem. A matheuristic using compromise put forward tackle proposed evaluated variety newly generated datasets which produces solutions that demonstrate importance appropriate balance both functions. robustness analysis considering fluctuations customer demand assessed Monte Carlo simulation. results show if standard deviation falls within 10% its average, unsatisfied insignificant, thus demonstrating stability configuration. invaluable information key towards helping senior management make relevant operational strategic decisions could impact on sustainability resilience networks.