Optimizing time–cost trade-off decisions in an interval transportation problem with multiple shipment options

This article makes an attempt to build on the extant literature time–cost trade-off in a transportation problem. The idea is agglomerate world of multiple shipment options along with uncertainty demand/supply requirements traditional set-up. introduces bi-objective model multi-choice cost and time coefficients interval demand supply constraints. Such framework more generalized provides much broader view decision-maker. research proposes efficient iterative algorithm for generating Pareto frontier that solves minimum flow problem at each iteration. special structure this network exploited obtain computationally results. proposed method applied real-world case study UPS Express Critical United States. analysis suggests significant savings objectives can be achieved over set-ups.