How the paper industry is devastating Pakistani environment: an application of the MILP and MOGA

The case studies are introduced in this study, highlighting freight transportation via road and road rail between satellite cities in Pakistan’s Punjab and Sindh provinces. The case study analysis contributes to developing environmentally friendly and cost-effective transportation solutions and reducing nitrous oxide (N₂O) and carbon dioxide (CO₂) emissions associated with road and intermodal freight transit. We developed a mixed-integer linear programming (MILP) model to formulate the bi-objective problem, including real-life constraints, emissions at starting nodes, ending notes, and between the arc. In the mathematical model, the cost and emissions functions are developed to minimize the primary and secondary objective functions in the road and intermodal transportation. Furthermore, five distinct sets (locations, starting stations, ending stations, transport orders, and transport service) with parameters relating to container movement between the starting and ending nodes are a necessary part of the MILP formulation. The multiobjective optimization problem is solved by metaheuristic techniques such as the multiobjective genetic algorithm as the goal of applying a metaheuristic algorithm is to find the search space to search the near to optimized solutions. The Pareto front solutions are provided for balancing the costs and emissions of transporting supplies from Punjab to Sindh using the MATLAB solver toolbox. We gathered data from one of Pakistan’s most well-known logistics service providers in the paper industry. According to the findings, intermodal transportation is 72% more cost-effective than road transportation. Additionally, by substituting intermodal transportation for road transportation, N₂O, and CO₂ emissions can be reduced by 74% and 57%, respectively.