رویکرد ترکیبی یکپارچه سازی نمودار وابستگی، تحلیل سلسله مراتبی و TOPSIS فازی برای برنامه ریزی تدارکات توسعه پایدار شهر

City logistics initiatives are steps taken by municipal administrations to ameliorate the condition of goods transport in cities and reduce their negative impacts on city residents and their environment. Examples of city logistics initiatives are urban distribution centers, congestion pricing, delivery timing and access restrictions. In this paper, we present a hybrid approach based on Affinity Diagram, AHP and fuzzy TOPSIS for evaluating city logistics initiatives. Four initiatives namely vehicle sizing restrictions, congestion charging schemes, urban distribution center and access timing restrictions are considered. The proposed approach consists of four steps. The first step involves identification of criteria for assessing performance of city logistics initiatives using Affinity Diagram. The results are four categories of criteria namely technical, social, economical and environmental. In step 2, a decision making committee comprising of representatives of city logistics stakeholders is formed. These stakeholders are shippers, receivers, transport operators, end consumers and public administrators. The committee members weight the selected criteria using AHP. In step 3, the decision makers provide linguistic ratings to the alternatives (city logistics initiatives) to assess their performance against the selected criteria. These linguistic ratings are then aggregated using fuzzy TOPSIS to generate an overall performance score for each alternative. The alternative with the highest score is finally chosen as most suitable city logistics initiative for improving city sustainability. In the fourth step, we perform sensitivity analysis to evaluate the influence of criteria weights on the selection of the best alternative. The proposed approach is novel and can be practically applied for selecting sustainable city logistics initiatives for cities. Another advantage is its ability to generate solutions under limited quantitative information. An empirical application of the proposed approach is provided.

Modern cities are facing congestion, lack of public space, huge waiting times, air pollution, and noise arising air from goods movement in cities. To maintain the economic growth of cities and meet customer demands, organizations are continually involved in production and distribution of goods; however, this has come at an unexpected cost of degradation of quality of life in modern cities [1]. To cope up with this growing crisis, municipal administrations are investing in sustainable city logistics initiatives to ameliorate the condition of goods transport in cities and reduce their negative impacts on city residents and their environment. Examples of these initiatives are urban distribution centers, congestion pricing, delivery timing and access restrictions. According to the Council of Logistics Management, [2], “Logistics is that part of the supply chain process that plans, implements, and controls the flow and storage of goods, services, and related information from the point of origin to the point of consumption in order to meet customer’s requirements”. The logistics associated with consolidation, transportation, and distribution of goods in cities is called city logistics. From a systems point of view, city logistics consists of many subsystems involving different stakeholders namely shippers, receivers, end consumers, transport operators and public administrators (see Fig. 1). The end-consumers are residents or the people that live and work in the metropolitan areas. Shippers (wholesalers) supply good to the receivers (retailers, shopkeepers) through transport operators (or carriers). Administrators represent the government or transport authorities whose objective is to resolve conflict between city logistics actors, while facilitating sustainable development of urban areas.In recent years, several studies have been conducted by researchers on city logistics planning and evaluation. Munuzuri et al. [3] presents a compilation of solutions that can be implemented by local administrations in order to improve freight deliveries in urban environments. Visser et al. [4] present a classification of public, private and public-private measures related to urban freight. The COST 321 Action [5] report categorizes urban freight transport measures as promising and less promising measures based on experts survey. Dablanc [6] brings forth difficulties in implementing logistical measures in European cities and proposes consideration of stakeholder involvement and interests in devising new policies and regulations. A detailed study of modeling approaches for evaluating and planning city logistics measures can be found in Taniguchi et al. [7] and Crainic et al. [8]. The existing studies on city logistics planning can be mainly classified into (a) survey based approaches, (b) simulation based approaches, (c) multicriteria decision making based approaches, (d) heuristics based approaches and (e) cost-benefit analysis based approaches. Allen et al. [9] conducted group discussions with companies to analyze the potential impacts of sustainable distribution measures in UK urban areas. Esser and Kurte [10] use empirical data from customer survey to analyze the impact of B2C e-commerce on transport in urban areas in Germany. Anderson et al. [11] conduct a survey study to investigate the operational, financial and environmental effects of city logistics policy measures. Thompson and Hassall [12] use ratings scores for evaluating urban freight projects. Patier and Alligier [13] use Delphi study and Structural Equation Modeling to assess the current and future effects of online retailing on city logistics in France. Quak et al. [14] use case studies of 14 Dutch organizations to investigate the impact of governmental time-window pressure on retailers’ logistical concepts and the consequential financial and environmental distribution performance. Studies on simulation based approaches involve simulation of urban freight over the road networks to assess their impacts. Barceló and Grzybowska [15] combine vehicle routing models and microscopic traffic simulation to model and evaluate city logistics applications. Taniguchi and Tamagawa [16] proposed a simulation based approach for evaluating city logistics measures considering the behavior of several stakeholders. Yamada and Taniguchi [17] use bilevel optimization model for representing the behavior of stakeholders associated with urban goods delivery. Taniguchi and Van Der Heijden [18] present a methodology for evaluating city logistics initiatives using a dynamic traffic simulation with optimal routing and scheduling. Awasthi and Proth [19] propose a system dynamics based approach for city logistics decision making. Segalou et al. [20] propose a traffic simulation model for environmental impact assessment of urban goods movement. Marquez and Salim [21] use scenario analysis to investigate the sensitivity of urban freight patterns to various greenhouse gas abatement policy measures. In multicriteria decision making based approaches, alternatives (city logistics initiatives) are evaluated against several weighted criteria and the alternative with the highest performance score considering all criteria is finally chosen. Examples of few multicriteria decision making techniques are AHP (Analytical Hierarchy Process), TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) etc. Kapros et al. [22] present a multicriteria approach for evaluating intermodal freight villages. Kunadhamraks and Hanaoka [23] use fuzzy AHP for evaluation of logistics performance for freight mode choice at an intermodal terminal. Application of metaheuristics for city logistics planning has been investigated by Rooijen et al. [24] who use VRPTW (Vehicle Routing Problem Under Time Windows) and genetic algorithm to model the impact of community level regulation on city logistics. Cost-benefit analysis approaches involve evaluation of alternatives for benefits (the higher the better) vs costs (the lower the better). Van Duin et al. [25] use cost benefit analysis for evaluating city distribution centre. The problem treated in this paper is practical in nature and inspired by growing congestion and space limitation problems arising in urban areas due to poorly managed goods distribution. We present a hybrid approach based on Affinity Diagram, AHP and fuzzy TOPSIS for evaluating city logistics initiatives. Affinity Diagram is used to generate criteria for selecting sustainable city logistics initiatives. AHP is used to generate criteria weights since they are known with precision by the city experts. Fuzzy TOPSIS is used for evaluating alternatives of city logistics planning since many of them are not known with certainty to the decision makers due to specific context of each city, no prior experience with alternatives, and lack of numeric data, thereby justifying the use of linguistic ratings and fuzzy theory in rating them. Besides it is much easier to represent performance of city logistics initiatives in linguistic terms such as good, very good, poor, very poor etc. than in numbers, therefore, linguistic assessments [26] are used in rating the performance of city logistics initiatives. Fuzzy set theory is used to model vagueness and uncertainty in decision making processes arising due to lack of complete information [27]. The rest of the paper is organized as follows. In Section 2, we present preliminaries of AHP, fuzzy set theory and fuzzy TOPSIS. In Section 3, we present our hybrid approach for evaluating city logistics initiatives. Section 4 presents an empirical application of the proposed approach. In the fifth and the last section, we present the conclusions and future work.

In this paper, we present a multi-criteria multi-stakeholder approach for evaluating city logistics initiatives under fuzzy environment. Four initiatives namely vehicle sizing restrictions, congestion charging schemes, urban distribution center and access timing restrictions are considered. These initiatives are evaluated by a decision making team comprising of representatives of city logistics stakeholders namely Shippers (Wholesalers), Receivers (Retailers/Shop Owners), End Users (Consumers), Transport Operators (Carriers) and Public Administrators. The evaluation process involves four steps. In step 1, the criteria for evaluating city logistics initiatives are identified using Affinity Diagram. These criteria are technical, economic, environmental and social. In the second step, the criteria and the sub-criteria are weighted by a committee of decision makers. AHP is used to rate the criteria. In the third step, the decision making committee provides linguistic ratings to the criteria, sub-criteria and the alternatives. Fuzzy TOPSIS is used to aggregate the ratings and generate an overall performance score for measuring the performance of each alternative (city logistics initiative). The alternative with the highest score is finally chosen. In the last step, we perform sensitivity analysis to determine the influence of criteria weights on the decision making process. The advantage of the proposed approach is its practical applicability and the ability to generate solutions under limited quantitative information. It can be applied in new cities with no prior experience with city logistics initiatives. The limitation of the proposed approach is that it is sensitive to the number of decision makers involved and their experience with city logistics, hence, their selection should be carefully done. Our future work involves validation of proposed model results by comparison with other techniques available for selection of sustainable city logistics planning alternatives in literature.