a b s t r a c tCollaboration planning among city logistics operators is important to achieve operational efficiency under municipal freight regulations such as access, sizing and timing restrictions etc. In this paper, we present a fuzzy BOCR-GRA approach for collaboration partner selection for city logistics planning under the presence of municipal freight regulations. A multi-step approach is proposed. In the first step, we identify collaboration partner evaluation criteria using BOCR framework. In the second step, linguistic assessment of criteria and alternatives (collaboration partners) is performed by a decision making committee. The linguistic data is treated via fuzzy triangular numbers for analytical processing. In the third step, alternatives are ranked using Gray Relational Analysis technique (GRA) and five BOCR scoring methods. The different alternative ranks are subject to veto and the alternative(s) with highest top ranks are considered for sensitivity analysis whereby we analyze the influence of changes in criteria weights and scoring methods on their ranks. If the rankings remain unchanged, then the veto retained alternative(s) are declared as winner(s) and recommended for collaboration. A numerical application is provided. This is one of the first works to address the collaboration partner selection problem in the context of city logistics under limited or lack of quantitative data. A comprehensive set of criteria are proposed and the best solution is generated using veto role on various scores obtained from BOCR and fuzzy GRA, thereby eliminating any bias arising from method selection.

City logistics involves movement of city goods in urban areas respecting the municipal and administrative guidelines. The key goals of city logistics planning are maximizing vehicle movement and utilization, while minimising vehicle emissions and traffic congestion. Collaboration is vital to managing city logistics operations efficiently. Collaboration can take place in the form of goods consolidation, sharing of resources, information sharing, and so on. Two categories of models are proposed to evaluate these collaboration strategies. At the macro level, we present the collaboration matrix model; and at the micro level, we present the operational level model. The macro-level model focuses on the strategic decision making process necessary for stakeholders' collaboration given the socio-cultural characteristics, economic, and environmental constraint factors, while the micro-level model applies the collaboration decision-making criteria derived from the macro-level analytic result to improve the activities of the city logistics operators. Results of the computational testing of our methodology on vehicle selection, goods to vehicle assignment, goods distribution and environmental impact assessment are discussed, showing that the collaboration strategies of stakeholders, if optimized, can improve city logistics operations. The proposed work is novel and has strong practical applicability for logistics planners and decision makers in planning right collaboration strategies for sustainable city logistics operations.

No abstract

No abstract

No abstract