Evaluation of Smart City Logistics Solutions

Abstract

The negative effects of goods flows realisation are most visible in urban areas as the places of the greatest concentration of economic and social activities. The main goals of this article were to identify the applicable Industry 4.0 technologies for performing various city logistics (CL) operations, establish smart sustainable CL solutions (SSCL) and rank them in order to identify those which will serve as the base points for future plans and strategies for the development of smart cities. This kind of problem requires involvement of multiple stakeholders with their opposing goals and interests, and thus multiple criteria. For solving it, this article proposed a novel hybrid multi-criteria decision-making (MCDM) model, based on BWM (Best-Worst Method) and CODAS (COmbinative Distance-based ASsessment) methods in grey environment. The results of the model application imply that the potentially best SSCL solution is based on the combination of the concepts of micro-consolidation centres and autonomous vehicles with the support of artificial intelligence and Internet of Things technologies. The main contributions of the article are the definition of original SSCLs, the creation of a framework and definition of criteria for their evaluation and the development of a novel hybrid MCDM model.

Smart Material Handling Solutions for City Logistics Systems

“…For this reason, in the last couple of decades, CL has been the subject of numerous research that has mainly dealt with identifying problems [4,5,10]; defining initiatives, concepts and measures to solve the problems [7,[11][12][13][14][15]; defining the scenarios of the development of CL systems [9,[16][17][18][19]; and developing and applying modern technologies in the field of CL [2,[20][21][22].…”

“…Tadić et al [38] analyzed the use of drones in CL. Tadić et al [20] proposed smart, sustainable CL solutions as a combination of various CL initiatives, measures, concepts and I 4.0 technologies (AV, UAV and robotics). They aimed to mitigate GHG emissions, urban congestion and other effects of unsustainable logistics.…”

“…Customers' demands in the city are characterized by a high frequency, a wide assortment, home delivery, individual delivery, smaller deliveries, delivery at certain time intervals, etc. [1][2][3][4][5][6]. In addition, CL trends, such as low driving speeds, short routes, stochastic vehicle downtime, limited space, inadequate traffic infrastructure and many others, are permanently present in customer service in the city [7].…”

Intermodal Terminal Subsystem Technology Selection Using Integrated Fuzzy MCDM Model

“…Although it is a relatively new method, it has found a very wide application in a very short time. In its conventional form or its fuzzy extension, independently or as part of a hybrid model, CODAS was used for 3PL (3rd Party Logistics) provider selection [49], the establishment of smart city solutions [50], supplier selection [51], personnel evaluation [52], facility location [53,54], most polluted cities ranking [55], vehicle selection [56], etc. However, the CODAS method has never been used in any form for the selection of handling technology in ITs, which is another research gap this paper is trying to cover.…”

“…establishment of smart city solutions [50], supplier selection [51], personnel evaluation [52], facility location [53,54], most polluted cities ranking [55], vehicle selection [56], etc. However, the CODAS method has never been used in any form for the selection of handling technology in ITs, which is another research gap this paper is trying to cover.…”