Traditional supply chain modelling tends to focus on singular objectives, with a predominant focus on cost. Within this discipline location-routing problems are one of the most researched categories in recent years. This study extends this paradigm to consider the multi-objective of cost and environmental impact in the form of carbon emissions. The focus of this study is on the design of a low-cost low-carbon structure for the demand side of supply chain networks.
This research has developed two-layer and three-layer multi-objective 0-1 mixedinteger AHP-integrated location-routing models. Disparate multi-objective Genetic Algorithm, Particle Swarm, and Simulated Annealing-based optimisers are used to execute these developed models. The main execution platform used is modeFRONTIER®, a multi-objective optimisation and design environment.
The main contributions from this research are 1) the modelling extension to include low carbon emissions; costs; demand as an objective function component; and the inclusion of the decision makers’ priority as a green constraint, 2)with regard to implementing these specific NP-hard models, a DoE-guided solution approach is used. Various heuristics/meta-heuristics are adopted and compared in terms of their efficiency, with the three-layer model being solved in two phases, 3) both sets of developed models are applied to the demand side of a dairy supply chain in Ireland
