A Carbon-Conscious Closed Loop Multi Objective p-Hub Location Problem

Abstract: With increasing demand for environmentally-friendly products and government legislation incentivizing sustainable means of production, companies now look to adapt and incorporate these demands in production. Remanufacturing has been in industry for many years now but research into optimizing remanufacturing networks (collections of manufacturing facilities, disposal sites, recycling centers, and distribution centers) have only recently come under investigation. Closed-loop supply chain, vehicle routing and inventory management optimization problems have generally implemented a Carbon Cap Trading (CCT) methodology to set limits to carbon emissions but not minimize these emissions explicitly. The major drawback of the traditional CCT model is that it does not incentivize companies to invest into greener technologies for their production systems, giving priority to established logistics networks over finding newer hubs which would prove more eco-friendly. The goal of this research is to efficiently minimize the carbon footprint of remanufacturing operations networks keeping costs under constraint: a mixed-integer programming model focusing on locating the various premises involved is developed to address this problem. An important aspect of this the problem is estimation of carbon emission of the plant and its suppliers in manufacturing, remanufacturing operations having a major impact on minimizing the objective value. The approach is demonstrated via optimal solution of a problem involving a glass manufacturing company (a p-Hub multi-objective location problem of manufacturing, distribution and recollection centers with given set of locations of which only p number of hubs are open for operations). Energy data of operations has been sourced from the US Energy Information Administration.