The famous vehicle routing issue has an offshoot called the periodic vehicle routing problem (PVRP). The problem of high-value
cargo transportation using PVRP that incorporates time windows and time spread limits (PVRP-TWTS) is tackled in this
research. Over the course of many planning periods, a fleet of diversely capacitated vehicles must fulfill customers' period-
specific expectations in the PVRP-TWTS. Due to security considerations, waiting time is not permitted for the cars, and client
arrival times should be erratic within their time slot throughout the planning periods. For the PVRP-TWTS, this research suggests
new models based on mixed-integer linear programming (MILP) and constraint programming (CP). In addition, we provide a
lower limit and other valid inequalities to bolster the MILP and CP models that have been suggested. In the operations research
community, CP is still less well-known than MILP, despite its usefulness for a variety of optimization issues. Utilizing CP's
efficacy in resolving the PVRP-TWTS is the primary goal of this research. Based on our research, this is the only publication to
date to provide a CP model for PVRP-TWTS. The issue may be better understood with a comparison of the CP and MILP
models. By making adjustments to the widely-used literature benchmark set, we assess how well the suggested MILP and CP
models perform. Extensive computational studies demonstrate that, when comparing solution quality, the CP model outperforms
the MILP model.