Final results. The chosen option is the fact that with weights = 0.05 y = 0.95 using a total cost17 of 21 of COP 12,103 (see Figure 9).Figure 9. Pareto frontier for the case study application. Figure 9. Pareto frontier for the case study application.2021, ten, x FOR PEER REVIEWLocations of theLocations of the transshipments ULS in establishes in two zones. Transshipm transshipments ULS is establishes is two zones. Transshipments ULS j1 and j2 are in zone 2, j2 are in zone 2, while transshipment ULS j3 is in zone 1 (see Figure ten). T ULS j1 and though transshipment ULS j3 is in zone 1 (see Figure ten). This location generates a violation of theviolationtimes at the three transshipments ULS. This ULS. T location generates a arrival of the arrival times at the three transshipments also generates delays for points of sale six and 9of sale 6 andand 77.13 of 23 respectively). also generates delays for points (68.31 min 9 (68.3119 min, 77.13 min, respective min and These outcomes These outcomes with the model are to by the decisionmaker. with the model are to be deemed be viewed as by the decisionmaker.Figure 10. Place Figure 10. Place of transshipment urban logistics spaces. of transshipment urban logistics spaces.5. Conclusions5. Conclusions Urban logisticsUrban logistics spaces (ULS) are logistics infrastructures that facilitate transport and spaces (ULS) are logistics infrastructures that facilitate transport and goods cities and their surroundings (peripheral locations). Therefore, some goods flows betweenflows in between cities and their surroundings (peripheral areas). As a result, some general traits for the ULS are (e.g., design, style, dimensions, flows, common traits for the ULS are assumed assumed (e.g.,dimensions, flows, stake stakeholders, distinct purposes of each ULS), as proposed in for the development of proholders, certain purposes of each and every ULS), as proposed in for the improvement of thethe proposed model. This paper developed biobjective mathematical model of twoechelon for posed model. This paper developed a a biobjective mathematical model of twoechelon for the place and distribution a number of goods in an urban context. Soft time windows the location and distribution ofof several goodsin an urban context. Soft time windows have been Propamocarb Technical Information applied to handle the arrival at each and every from the related nodes at each level of the distribution procedure. In were applied to control the arrival at every on the related nodes at each degree of the distribution procedure.addition, the the impacttime windows on the the variationvelocities for for travel process Moreover, impact of of time windows on variation of of velocities the the travel approach in each and every arc is evident. The model was validated having a set of instances corresponding to two theoretical scenarios. A set of variations had been generated for the weights related with the objectives of minimizing expenses by distribution and relocation, along with the second objective related with minimizing expenses by violation of time windows.Axioms 2021, 10,18 ofin each arc is evident. The model was validated having a set of Methotrexate disodium MedChemExpress situations corresponding to two theoretical scenarios. A set of variations have been generated for the weights connected together with the objectives of minimizing fees by distribution and relocation, plus the second objective related with minimizing fees by violation of time windows. The results showed comparable behavior for both situations. The variations that assigned greater weight for the very first objec.