scholarly journals A MultiObjective Optimization Approach for Integrated Timetabling and Vehicle Scheduling with Uncertainty

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Yindong Shen ◽  
Wenliang Xie ◽  
Jingpeng Li

The timetabling problem (TTP) and vehicle scheduling problem (VSP) are two indispensable problems in public transit planning process. They used to be solved in sequence; hence, optimality of resulting solutions is compromised. To get better results, some integrated approaches emerge to solve the TTP and VSP as an integrated problem. In the existing integrated approaches, the passenger comfort on bus and the uncertainty in the real world are rarely considered. To provide better service for passengers and enhance the robustness of the schedule to be compiled, we study the integrated optimization of TTP and VSP with uncertainty. In this paper, a novel multiobjective optimization approach with the objectives of minimizing the passenger travel cost, the vehicle scheduling cost, and the incompatible trip-link cost is proposed. Meanwhile, a multiobjective hybrid algorithm, which is a combination of the self-adjust genetic algorithm (SGA), large neighborhood search (LNS) algorithm, and Pareto separation operator (PSO), is applied to solve the integrated optimization problem. The experimental results show that the approach outperforms existing approaches in terms of service level and robustness.

Forests ◽  
2019 ◽  
Vol 10 (8) ◽  
pp. 687 ◽  
Author(s):  
Bont ◽  
Maurer ◽  
Breschan

Cable yarding is the most commonly used technique for harvesting timber from steep terrain in central Europe. During the planning process, one important task is to define the cable road layout. This means that the harvesting technology and cable road location must be specified for a given timber parcel. Although managers must minimize harvesting costs, it is even more important that such work on forests reduces the potential for damage to the residual stand and ensures that environmental conditions remain suitable for regeneration. However, current methods are geared only toward minimizing harvesting costs and are computationally demanding and difficult to handle for the end user. These limitations hinder broad application of such methods. Further, the underlying productivity models used for cost estimation do not cover all conditions of an area and they cannot be applied over a whole harvesting area. To overcome these shortcomings, we present: (1) a multiobjective optimization approach that leads to realistic, practicable results that consider multiple conflicting design objectives, and (2) a concept for an easy-to-use application. We compare the practical applicability and performance of the results achieved with multiobjective optimization with those achieved with single-objective (cost-minimal) optimization. Based on these points, we then present and discuss a concept for a user-friendly implementation. The model was tested on two sites in Switzerland. The study produced the following major findings: (1) Single-objective alternatives have no practical relevance, whereas multiobjective alternatives are preferable in real-world applications and lead to realistic solutions; (2) the solution process for a planning unit should include analysis of the Pareto frontier; and (3) results can only be made available within a useful period of time by parallelizing computing operations.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 223782-223796
Author(s):  
Xixing Li ◽  
Hongtao Tang ◽  
Zhipeng Yang ◽  
Rui Wu ◽  
Yabo Luo

Author(s):  
Ashraf O. Nassef

Auxetic structures are ones, which exhibit an in-plane negative Poisson ratio behavior. Such structures can be obtained by specially designed honeycombs or by specially designed composites. The design of such honeycombs and composites has been tackled using a combination of optimization and finite elements analysis. Since, there is a tradeoff between the Poisson ratio of such structures and their elastic modulus, it might not be possible to attain a desired value for both properties simultaneously. The presented work approaches the problem using evolutionary multiobjective optimization to produce several designs rather than one. The algorithm provides the designs that lie on the tradeoff frontier between both properties.


2008 ◽  
Vol 26 (16) ◽  
pp. 2969-2976 ◽  
Author(s):  
Ademar Muraro ◽  
Angelo Passaro ◽  
Nancy Mieko Abe ◽  
Airam Jonatas Preto ◽  
Stephan Stephany

Author(s):  
Andrew Guthrie ◽  
Yingling Fan ◽  
Kirti Vardhan Das

Accessibility analysis can have important implications for understanding social equity in transit planning. The emergence and the increasingly broad acceptance of the general transit feed specification (GTFS) format for transit route, stop, and schedule data have revolutionized transit accessibility research by providing researchers with a convenient, publicly available source of data interoperable with common geographic information system (GIS) software. Existing approaches to GTFS-based transit analysis, however, focus on currently operating transit systems. With major transit expansions across the nation and around the world increasing in number and ambition, understanding the accessibility impacts of proposed projects in their early planning stages is crucial to achieving the greatest possible social benefit from these massive public investments. This paper describes the development of a hypothetical transit network based on current GTFS data and proposed 2040 transit improvements for the Twin Cities region of Minneapolis–Saint Paul, Minnesota, as well as its use as a sketch planning tool in exploring the proposed system’s impacts on access to job vacancies from historically disadvantaged areas. This research demonstrates the importance of accessibility analysis in planning a transit system that increases opportunity for marginalized workers and concludes by calling for broader, easier access to accessibility analysis for practitioners and community groups to refine the early stages of the transit planning process and democratize an increasingly crucial transit planning tool.


2017 ◽  
Vol 58 ◽  
pp. 732-741 ◽  
Author(s):  
Yu-Jun Zheng ◽  
Yue Wang ◽  
Hai-Feng Ling ◽  
Yu Xue ◽  
Sheng-Yong Chen

Author(s):  
Lifang Zeng ◽  
Dingyi Pan ◽  
Shangjun Ye ◽  
Xueming Shao

A fast multiobjective optimization method for S-duct scoop inlets considering both inflow and outflow is developed and validated. To reduce computation consumption of optimization, a simplified efficient model is proposed, in which only inflow region is simulated. Inlet pressure boundary condition of the efficient model is specified by solving an integral model with both inflow and outflow. An automated optimization system integrating the computational fluid dynamics analysis, nonuniform rational B-spline geometric representation technique, and nondominated sorting genetic algorithm II is developed to minimize the total pressure loss and distortion at the exit of diffuser. Flow field is numerically simulated by solving the Reynolds-averaged Navier–Stokes equation coupled with k–ω shear stress transport turbulence model, and results are validated to agree well with previous experiment. S-duct centreline shape and cross-sectional area distribution are parameterized as the design variables. By analyzing the results of a suggested optimal inlet chosen from the obtained Pareto front, total pressure recovery has increased from 97% to 97.4%, and total pressure distortion DC60 has decreased by 0.0477 (21.7% of the origin) at designed Mach number 0.7. The simplified efficient model has been validated to be reliable, and by which the time cost for the optimization project has been reduced by 70%.


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