外文翻译--公交路线网络设计问题：回顾节选(编辑修改稿)

外文翻译--公交路线网络设计问题：回顾节选(编辑修改稿)内容摘要：

services provided. The “Parameters” layer describes the operating environ ment and includes both the design variables expected to be de rived for the transit work (route layouts, frequencies) as well as environmental and operational parameters affecting and con straining that work (for example, allowable frequencies, de sired load factors, fleet availability, demand characteristics and patterns, and so on). Finally, the “Methodology” layer covers the logical–mathematical framework and algorithmic tools necessary to formulate and solve the TRNDP. The proposed structure fol lows the basic concepts toward setting up a TRNDP: deciding upon the objectives, selecting the transit work items and char acteristics to be designed, setting the necessary constraints for the operating environment, and formulating and solving the problem. TRNDP: Objectives Public transportation serves a very important social role while attempting to do this at the lowest possible operating cost. Objec tives for designing daily operations of a public transportation sys tem should enpass both angles. The literature suggests that most studies actually focus on both the service and economic efficiency when designing such a system. Practical goals for the TRNDP can be briefly summarized as follows (Fielding 1987。 van Oudheudsen et al. 1987。 Black 1995): (1) user benefit maxi mization。 (2) operator cost minimization。 (3) total welfare maxi mization。 (4) capacity maximization。 (5) energy conservation— protection of the environment。 and (6) individual parameter optimization. Mandl (1980) indicated that public transportation systems have different objectives to meet. He mented, “even a single objective problem is difficult to attack” (p. 401). Often, these objectives are controversial since cutbacks in operating costs may require reductions in the quality of services. Van Nes and Bovy (2020) pointed out that selected objectives influence the attrac tiveness and performance of a public transportation work. Ac cording to Ceder and Wilson (1986), minimization of generalized cost or time or maximization of consumer surplus were the most mon objectives selected when developing transit work de sign models. Berechman (1993) agreed that maximization of total welfare is the most suitable objective for designing a public trans portation system while Van Nes and Bovy (2020) argued that the minimization of total user and system costs seem the most suit able and less plicated objective (pared to total welfare), while profit maximization leads to nonattractive public transpor tation works. As can be seen in Table 1, most studies seek to optimize total welfare, which incorporates benefits to the user and to the system. User benefits may include travel, access and waiting cost minimi zation, minimization of transfers, and maximization of coverage, while benefits for the system are maximum utilization and quality of service, minimization of operating costs, maximization of prof its, and minimization of the fleet size used. Most monly, total welfare is represented by the minimization of user and system costs. Some studies address specific objectives from the user, the operator, or the environmental perspective. Passenger conve nience, the number of transfers, profit and capacity maximization, travel time minimization, and fuel consumption minimization are such objectives. These studies either attempt to simplify the 5 plex objective functions needed to setup the TRNDP (Newell 1979。 Baaj and Mahmassani 1991。 Chakroborty and Dwivedi 2020), or investigate specific aspects of the problem, such as ob jectives (Delle Site and Fillipi 2020), and the solution methodol ogy (Zhao and Zeng 2020。 Yu and Yang 2020). Total welfare is, in a sense, a promise between objectives. Moreover, as reported by some researchers such as Baaj and Mahmassani (1991), Bielli et al. (2020), Chackroborty and Dwivedi (2020), and Chakroborty (2020), transit work design is inherently a multiobjective problem. Multiobjective models for solving the TRNDP have been based on the calculation of indi cators representing different objectives for the problem at hand, both from the user and operator perspectives, such as travel and waiting times (user), and capacity and operating costs (operator). In their multiobjective model for the TRNDP, Baaj and Majmas sani (1991) relied on the planner’s judgment and experience for selecting the optimal public transportation work, based on a set of indicators. In contrast, Bielli et al. (2020) and Chakroborty and Dwivedi (2020), bined indicators into an overall, weighted sum value, which served as the criterion for determining the op timal transit work. TRNDP: Parameters There are multiple characteristics and design attributes to con sider for a realistic representation of a public transportation work. These form the parameters for the TRNDP. Part of these parameters is the problem set of decision variables that define its layout and operational characteristics (frequencies, vehicle size,。