A realistic and sustainable logistics transportation planning: a new cost model, meta-heuristic solving approach, and results

Accurate logistics cost enables efficient and cost-effective planning of transportation systems. It facilitates the fast, on-time, and seamless transportation of goods between the cities. Existing cost models are based on the unit transportation cost of goods, which could be more realistic and accurate. In this work, we introduce a new cost function based on the unit transportation cost of a truck to overcome the undercharging or overcharging issues in the existing cost functions. The proposed cost function best suits the government and industry when developing the facilities. This work also presents the logistic transportation problem, formulation of a cost function using integer programming, and methodology to solve the transportation problem using meta-heuristic algorithms. In addition, we construct a new transportation problem for one district-one product (ODOP) using real-world scenarios and data. ODOP is an initiative of the Uttar Pradesh Government for the balanced economic development of the state in India. We solve this 18 cities problem using eight meta-heuristic algorithms. Our experimental simulation finds an optimal logistics cost of Rs. 2159140.00/- for four logistics hubs and 14 distribution/collection centres. Our observation also identifies the dependency of network configuration over various factors like establishment/rental and operational cost, the unit cost of transportation, and the capacity of vehicles instead of only on product supply and demand of goods/products. Our evaluation also reports an 80% consistent result by the anti-predatory nature-inspired algorithm compared to the other state-of-the-art algorithms.