With the popularity and development of mobile Internet, new transportation network services such as customized buses are expected to become a new way of popular transportation in crowded metropolises. In this paper, w...
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With the popularity and development of mobile Internet, new transportation network services such as customized buses are expected to become a new way of popular transportation in crowded metropolises. In this paper, we propose a real-time customized bus routes design model. We divide the proposed model into two-stage problem to solve. The first stage problem is the vehicle route problem with time window (VRPTW), and the second stage problem is bilateral matching problem. For the first stage, the column generation algorithm is used to solve the problem. For the second stage, we solve it by the improved H-R bilateral matching algorithm. Finally, data on customized bus in Tianjin city of China are used to verify the accuracy of the real-time customized bus routes design model. The optimized results show that the average attendance rate has reached 70.8%, and the service rate of passenger has reached 88.5%. The results have proved that the real-time customized bus routes design model has a practical applicability in operation. (C) 2021 Elsevier B.V. All rights reserved.
The exact solution and heuristic solution have their own strengths and weaknesses on solving the Vehicle Routing Problems with Time Windows (VRPTW). This paper proposes a hybrid column generation algorithm with Metahe...
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The exact solution and heuristic solution have their own strengths and weaknesses on solving the Vehicle Routing Problems with Time Windows (VRPTW). This paper proposes a hybrid column generation algorithm with Metaheuristic Optimization (CGAMO) to overcome their weaknesses. Firstly, a Modified Labelling algorithm (MLA) in the sub-problem of path searching is analysed. And a search strategy in CGAMO based on the demand of sub-problem is proposed to improve the searching efficiency. While putting the paths found in the sub-problem into the main problems of CGAMO, the iterations may fall into endless loops. To avoid this problem and keep the main problems in a reasonable size, two conditions on saving the old paths in the main problem are used. These conditions enlarge the number of constraints considered in the iterations to strengthen the limits of dual variables. Through analysing the sub-problem, we can find many useless paths that have no effect on the objective function. Secondly, in order to reduce the number of useless paths and improve the efficiency, this paper proposes a heuristic optimization strategy of CGAMO for dual variables. It is supposed to accelerate the solving speed from the view of on the dual problem. Finally, extensive experiments show that CGAMO achieves a better performance than other state-of-the-art methods on solving VRPTW. The comparative experiments also present the parameters sensitivity analysis, including the different effects of MLA in the different path selection strategies, the characteristics and the applicable scopes of the two path-keeping conditions in the main problem.
The evolution of urban transportation systems is increasingly driven by the integration of rail, bus, and walking pathways, forming a cohesive service network. This urban rail-bus-walk service network integration is p...
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The evolution of urban transportation systems is increasingly driven by the integration of rail, bus, and walking pathways, forming a cohesive service network. This urban rail-bus-walk service network integration is pivotal in addressing urban challenges and ensuring seamless mobility. Nevertheless, the effectiveness of such integrated systems depends on their accessibility and the willingness of individuals to take them as their primary transportation mode. In the context of climate change, extreme heat events pose an increasing threat to passenger comfort and health, which in turn, affects individuals' decisions to use public transit. Additionally, walking to transit stops or waiting for transportation becomes more challenging during such extreme heat conditions. This paper tackles the challenge of comprehensively addressing the evolving issues related to public transit accessibility in response to rising temperatures, an area of research that has received limited attention until now. This paper introduced an approach aimed at optimizing the urban rail-bus-walk service network with a focus on both accessibility and heat exposure considerations. By calculating the transportation accessibility level under varying temperature conditions and identifying its vulnerability to high temperatures, this paper presents a methodology to enhance the transit service. Such improvement involves not only adjustments to the integration network but also considering of cooling facilities, such as shaded routes and shelters. columngeneration is applied to solve this problem and the optimization result demonstrates improvement of accessibility under the extreme heat condition.
Internet protocol television (IPTV) advertising has the characteristics of both traditional TV and online advertising and mainly sells impressions through signed guaranteed contracts with advertisers. In this study, w...
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Internet protocol television (IPTV) advertising has the characteristics of both traditional TV and online advertising and mainly sells impressions through signed guaranteed contracts with advertisers. In this study, we applied the reach and frequency (R&F) contract to the IPTV sales model. Through the R&F contract, advertisers can specify the expected number of unique individuals reached and the frequency cap of the advertisements seen by each user. Considering the lack of user demographic information, we propose using viewing program information instead as the basis for user classification in targeted advertising. Advertising allocation models for two-layer optimization are established. In the upper layer optimization, the advertising allocation proportion is optimized for all user types to minimize the publisher's under-delivery and nonrepresentativeness of advertising delivery among user types. In the lower layer optimization, the impact of repeated advertising on user purchase probability is considered. The specific allocation of advertisements is optimized for each user type to maximize the expected number of buyers without violating the optimization results of the upper layer optimization. A repeated exposure-based hierarchical columngeneration (REHCG) algorithm is used to address the IPTV advertising scheduling problem. Numerical experiments based on actual data from the IPTV industry show that the REHCG algorithm obtains high-quality results for IPTV advertising scheduling.
With the growing traffic of containerized shipping worldwide, container liners have seen increasing cooperation. Slot co-chartering has drawn wide attention as a way of cooperation within liner alliances. However, lin...
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With the growing traffic of containerized shipping worldwide, container liners have seen increasing cooperation. Slot co-chartering has drawn wide attention as a way of cooperation within liner alliances. However, liners face the issue of finding proper measures to optimize alliance operations. In response to this, this paper compre-hensively considers shipping capacity dispatch for containerized shipping companies within liner alliances. First, we explained the general rules of liner shipping dispatch and analyzed the interfering factors. Second, we created a liner shipping capacity dispatch model without consideration of slot co-chartering costs and a liner shipping capacity dispatch model with consideration of slot co-chartering costs and proposed a new column generation algorithm to solve both problems. Third, we tested our algorithm in a real case of a large Chinese containerized shipping company, which belongs to Ocean Alliance, and an optimal ship dispatch strategy on relevant routes and a decision on optimal slot chartering can be reached. Computational results indicate that the proposed column generation algorithm exhibits effective and efficient performance for large-scale slot co-chartering in liner shipping.
PurposeTo incorporate four-dimensional computed tomography (4DCT)-based ventilation imaging into intensity-modulated radiation therapy (IMRT) treatment planning for pulmonary functional avoidance. Methods and Material...
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PurposeTo incorporate four-dimensional computed tomography (4DCT)-based ventilation imaging into intensity-modulated radiation therapy (IMRT) treatment planning for pulmonary functional avoidance. Methods and MaterialsNineteen locally advanced lung cancer patients are retrospectively studied. 4DCT images are employed to create ventilation maps for each patient via a density-change-based algorithm with mass correction. The regional ventilation is directly incorporated into the mathematical formulation of a direct aperture optimization model in IMRT treatment planning to achieve functional avoidance and a voxel-based treatment plan. The proposed functional avoidance planning and voxel-based planning are compared to the conventional treatment planning approach purely based on the anatomy of patients. Paired sample t-tests are conducted to see whether dosimetric differences among the three approaches are significant. ResultsSimilar planning target volume (PTV) coverage is achieved by anatomical, functional avoidance, and voxel-based approaches. The voxel-based treatment planning performs better than both functional avoidance and anatomical planning to the lung. For a total lung, the average volume reductions in a functional avoidance plan from an anatomical plan, a voxel-based plan from an anatomical plan, and a voxel-based plan from a functional avoidance plan are 7.0% , 16.8%, and 10.6%, respectively for V-40;and 0.4%, 6.4%, and 6.0%, respectively for mean Lung Dose (MLD). For a functional lung, the reductions are 8.8% , 17.2%, and 9.2%, respectively, for fV(40);and 1.1%, 6.2%, and 5.2%, respectively, for functional mean lung dose (fMLD). These reductions are obtained without significantly increasing doses to other organs-at-risk. All the pairwise treatment planning comparisons for both total lung and functional lung are statistically significant (p-value
Combined cooling, heating, and power (CCHP) microgrids are a special form of a microgrid that is attracting increasing attention. This study contributes to the goal of minimising the operation cost of CCHP microgrids ...
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Combined cooling, heating, and power (CCHP) microgrids are a special form of a microgrid that is attracting increasing attention. This study contributes to the goal of minimising the operation cost of CCHP microgrids by proposing a hierarchical two-stage robust optimisation dispatch model for multiple CCHP microgrid systems. The uncertainties associated with wind power output, electric power, heating, and cooling loads, and transmission line failures are considered in the proposed model. Moreover, the electricity purchasing and selling prices of each microgrid are independently determined. The proposed model applies the outputs of fuel cells, energy storage devices, and gas turbines, the distribution factor of waste heat, and the power transmission between the microgrids and an external grid as control variables. The optimised dispatch problem is solved using McCormick envelopes relaxation and a novel column and constraint generationalgorithm that provides enhanced optimisation performance by implementing co-evolutionary theory. In this way, the microgrid system is divided into several sections, and each section is represented as an individual min-max-min problem. The rationality and validity of the proposed model and the superiority of the solution performance of the improved algorithm are verified through simulation case studies involving a system composed of four CCHP microgrids.
It is an effective way to regard the electric vehicles as the demand response for reducing the negative impact of large-scale introduction on the power system. Aiming at the microgrid with demand response, the adaptiv...
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It is an effective way to regard the electric vehicles as the demand response for reducing the negative impact of large-scale introduction on the power system. Aiming at the microgrid with demand response, the adaptive uncertainty sets-based two-stage robust optimisation method is established in this study. The coordination of micro-gas turbine, energy storage, and demand response etc. are considered in the economic dispatch model. To effectively consider the uncertain variable contained in the microgrid, the concept of adaptive uncertainty sets is proposed in this study. The uncertainty sets are achieved by the long short-term memory network and modified fuzzy information granulation. To handle the adaptive uncertainty sets-based robust optimisation model, the column and constraint generationalgorithm and strong duality theory are introduced to decompose the model into a master problem and a subproblem with mixed-integer linear structure. To verify the performance of the proposed adaptive uncertainty sets-based two-stage robust optimisation method, measured data from a plateau city of China are introduced in the simulation test. The simulation results demonstrate the effectiveness of the model and solution strategy.
In recent years,the online advertising industry has developed *** scholars have carried out research on how to formulate an optimal advertising ***,in the process of advertising,too redundant advertising often causes ...
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In recent years,the online advertising industry has developed *** scholars have carried out research on how to formulate an optimal advertising ***,in the process of advertising,too redundant advertising often causes customers' ***,it is necessary to ensure that the number of advertisements assigned by each user is within a reasonable range to maximize advertising *** the background of IPTV guaranteed contract,this paper studies the advertising planning problem considering the advertising effect caused by repeated *** order to solve this large-scale linear programming problem,an approach based on column generation algorithm is presented in this ***,experiment based on actual case shows the effectiveness of the algorithm.
In perpendicular layout terminals, containers initially stored near the landside need to be strategically relocated to the seaside for vessel loading. This study investigates this process, referred to as trans-marshal...
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