<p>This paper discusses a real-world, time and cost-minimizing multi-objective multi-item solid transportation problem of fertilizers for Telangana, India. The challenge is predominantly formulated based on actual data, encompassing the quantity available in seven production units, the demand in 33 districts, and the transportation of three items facilitated by two conveyances. The fertilizer transportation problem is addressed through two evolutionary algorithms, which involve generating a population of solutions using an initialization algorithm and then applying a penalty-based elitist non-dominated sorting algorithm (NSGA-II) and constrained NSGA-II for further optimization. A comparison between the top three Pareto fronts achieved with penalty-based NSGA-II and those obtained from constrained NSGA-II is presented, and the superiority of the penalty method is demonstrated. The Pareto solutions and comparisons are graphically depicted using a time-versus-cost plot. This research primarily focuses on finding feasible supply chains while maintaining the cost and time of a four-dimensional transportation problem simultaneously. It will prove beneficial to researchers and practitioners by providing practical solutions for selecting an appropriate supply chain that aligns with their budget or time constraints. The results obtained will be valuable for logistic companies as they can effectively organize transportation based on the specific conveyance utilized in each supply chain.</p>