An effective evolutionary algorithm for solving uncertain fixed charge transportation problem with damageable items

This paper aims to showcase the potential application of the metaheuristic approach Quadratic Approximation based Jaya (JaQA) in addressing a single-objective uncertain Fixed Charge Transportation Problem with Damageable items (FCTPD). The incorporation of uncertainties and damage rates for items adds realism to the selected problem model. Subsequently, a comprehensive examination of the FCTPD model is conducted, considering both expected value and chance-constrained cases based on uncertainty theory. Equivalent deterministic formulations are considered for these scenarios. The performance of JaQA is comprehensively benchmarked on a set of ten popular benchmarks of single-objective fixed charge transportation problems (FCTP) from the OR library. In addition to this, it is also evaluated on the deterministic forms of the expected value and chance-constrained cases, and the computational results are compared with other widely recognized approaches such as Jaya algorithm, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for five numerical instances A thorough investigation of statistical, convergence, and sensitivity analysis are presented to shed light on the efficacy and stability levels of JaQA over its counterparts. The simulation outcomes and exhaustive statistical analysis show that for all the problems considered, JaQA performed better out of GA, PSO, and Jaya. More specifically, it indicated that the utilization of JaQA provided significant profit maximization of the transportation system, thereby ensuring a promising value of the optimal solution.