Abstract:
Consideration of environmental and economic aspects in supply chain design is required to reduce negative impacts on the environment caused by the increasing levels of industrialization. In this thesis work, a new transportation model is proposed to deal with the trade-offs among environmental effect and supply chain performance related issues. The new approach incorporates an open loop transportation network to accommodate a multi-objective optimization mathematical model to minimize overall costs, delivery time and carbon footprint while previous models did not consider the environmental aspects. The mathematical model is developed by assuming deterministic and satisfied demand. A real life transportation problem has been selected for case study and model validation rather than using hypothetical data. The problem has been solved using Non-dominated Sorting Genetic Algorithm-II (NSGA-II), a fast and elitist algorithm suggested by many researchers for this type of multi objective optimization problems. The optimum solutions and trade-offs among the objective functions have been shown in a pareto front which can be used as a supporting tool for supply chain practitioners and decision makers for a better sustainable transportation network solution.