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IEEE OPEN JOURNAL OF THE COMPUTER SOCIETY 2023年第1期4卷 1-12页

作者： Zhao, Xiao Chao, Yuyan Zhang, Hui Yao, Bin He, Lifeng Shaanxi Univ Sci & Technol Artificial Intelligence Inst Sch Elect Informat & Artificial Intelligence Xian 710021 Peoples R China Nagoya Sangyo Univ Grad Sch Environm Management Owariasa Shi 4888711 Japan Aichi Prefectural Univ Grad Sch Informat Sci & Technol Nagakute 4801198 Japan

Conventional voxel-based algorithms for labeling connected components in 3D binary images use the same mask to process all object voxels. To reduce the number of times that neighboring voxels are checked when object voxels are processed, we propose an algorithm that uses two different masks for processing two different types of object voxels. One type of mask is used when the voxel preceding the object voxel being processed is an object voxel, and the other type is used otherwise. In either case, an optimal order is used for checking the voxels in the corresponding mask. Experimental results demonstrate that our proposed algorithm checked fewer voxels, and was more efficient than conventional algorithms.

关键词： Three-dimensional displays labeling Image resolution Medical services Medical diagnostic imaging Artificial intelligence Transforms Computer vision connected component labeling algorithm 3D binary image

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A Bucket Graph-Based labeling algorithm with Application to Vehicle Routing

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TRANSPORTATION SCIENCE 2021年第1期55卷 4-28页

作者： Sadykov, Ruslan Uchoa, Eduardo Pessoa, Artur INRIA Bordeaux Sud Ouest F-33405 Talence France Univ Bordeaux Inst Math F-3340 Talence France Univ Fed Fluminense Engn Prod BR-24210240 Niteroi RJ Brazil

We consider the shortest path problem with resource constraints arising as a subproblem in state-of-the-art branch-cut-and-price algorithms for vehicle routing problems. We propose a variant of the bidirectional label-correcting algorithm in which the labels are stored and extended according to the so-called bucket graph. This organization of labels helps to significantly decrease the number of dominance checks and the running time of the algorithm. We also show how the forward/backward route symmetry can be exploited and how to eliminate arcs from the bucket graph using reduced costs. The proposed algorithm can be especially beneficial for vehicle routing instances with large vehicle capacity and/or with time window constraints. Computational experiments were performed on instances from the distance-constrained vehicle routing problem, including multidepot and site-dependent variants, on the vehicle routing problem with time windows, and on the "nightmare" instances of the heterogeneous fleet vehicle routing problem. Significant improvements over the best algorithms in the literature were achieved, and many instances could be solved for the first time.

关键词： labeling algorithm shortest path with resource constraints routing

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Block-Based Connected-Component labeling algorithm Using Binary Decision Trees

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SENSORS 2015年第9期15卷 23763-23787页

作者： Chang, Wan-Yu Chiu, Chung-Cheng Yang, Jia-Horng Natl Def Univ Chung Cheng Inst Technol Dept Elect & Elect Engn Taoyuan 33551 Taoyuan County Taiwan

In this paper, we propose a fast labeling algorithm based on block-based concepts. Because the number of memory access points directly affects the time consumption of the labeling algorithms, the aim of the proposed algorithm is to minimize neighborhood operations. Our algorithm utilizes a block-based view and correlates a raster scan to select the necessary pixels generated by a block-based scan mask. We analyze the advantages of a sequential raster scan for the block-based scan mask, and integrate the block-connected relationships using two different procedures with binary decision trees to reduce unnecessary memory access. This greatly simplifies the pixel locations of the block-based scan mask. Furthermore, our algorithm significantly reduces the number of leaf nodes and depth levels required in the binary decision tree. We analyze the labeling performance of the proposed algorithm alongside that of other labeling algorithms using high-resolution images and foreground images. The experimental results from synthetic and real image datasets demonstrate that the proposed algorithm is faster than other methods.

关键词： connected components labeling algorithm decision tree scan mask

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An exact branch-and-price-and-cut algorithm for a practical and large-scale dial-a-ride problem

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JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 2025年第6期76卷 1125-1139页

作者： Karimi, Mohammad Camiat, Fanny Desaulniers, Guy Gendreau, Michel Polytech Montreal Montreal PQ Canada CIRRELT Montreal PQ Canada GIRO Inc Montreal PQ Canada GERAD Montreal PQ Canada

Vehicle routing problems are encountered in various practical transportation scenarios. One such problem is the dial-a-ride problem (DARP), which involves transporting efficiently passengers from their origin to their destination and whose objective is to design vehicle routes minimizing total costs and accommodating all pickup-and-delivery requests. The solution must also adhere to capacity limitations, time windows, and a maximum ride time for each passenger. This paper proposes an exact branch-price-and-cut algorithm to solve a practical variant of the DARP, where both the passengers and vehicle fleet are heterogeneous, and other practical constraints such as break requirements and maximum route duration are imposed. In this algorithm, column generation which alternates between solving a master problem and subproblems, is used to compute lower bounds in the search tree. We develop a labeling algorithm to efficiently handle these subproblems. The effectiveness of the algorithm is evaluated on a real-world case study involving 849 heterogeneous passengers and more than 70 available vehicles, as well as on 10 smaller instances (with 300 to 820 trips) extracted from another very large real-world dataset. To the best of our knowledge, this 849-trip instance is the largest DARP instance reported to be solved to optimality in the literature.

关键词： Practical dial-a-ride problem break requirements branch-price-and-cut labeling algorithm

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Optimizing the Transport of Organs for Transplantation

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COMPUTERS & OPERATIONS RESEARCH 2025年 176卷

作者： Balster, Isaac Caetano, Joyce Azevedo Ribeiro, Glaydston Mattos Bahiense, Laura Fed Univ Rio Janeiro Alberto Luiz Coimbra Inst Grad Studies & Res Engn Transport Engn Program Rio De Janeiro Brazil Fed Univ Rio Janeiro Alberto Luiz Coimbra Inst Grad Studies & Res Engn Syst Engn & Comp Sci Program Transport Engn Program Rio De Janeiro Brazil

As an organ becomes available for transplantation, a recipient must be selected. Usually, donor and recipient are geographically apart. Therefore, the transport of the organ must be planned and executed within the time window imposed by the maximum preservation time of the organ, which can impact recipient selection. The Cold Ischemia Time- CIT, that is the time elapsed between the surgical removal of the organ and its transplantation, must be the minimum possible to improve the transplantation success. In this sense, the air transport becomes the best option and, sometimes, it is the only way to deliver the organ before perishing. The planning of an organ transportation means choosing, among thousands of possible sequences of flights, the option that delivers the organ faster to its destination. This problem can be modeled as a resource constrained shortest path. Given the urgency and importance of this task, which is solved manually in Brazil, we present a labeling algorithm to find the optimal sequence of flights. Computational tests performed on 25 Brazilian real cases showed a reduction, on average, of 37,46% for the CITs and 44,17% for the transport times.

关键词： Organ transplantation Organ transportation labeling algorithm Resource constrained shortest path

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Partial dominance in branch-price-and-cut algorithms for vehicle routing and scheduling problems with a single-segment tradeoff

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OR SPECTRUM 2024年第4期46卷 1063-1097页

作者： Faldum, Stefan Machate, Sarah Gschwind, Timo Irnich, Stefan Johannes Gutenberg Univ Mainz Chair Logist Management Gutenberg Sch Management & Econ Jakob Welder Weg 9 D-55128 Mainz Germany RPTU Kaiserlautern Landau Chair Logist Sch Business & Econ Gottlieb Daimler Str 42 D-67663 Kaiserslautern Germany

For many variants of vehicle routing and scheduling problems solved by a branch-price-and-cut (BPC) algorithm, the pricing subproblem is an elementary shortest-path problem with resource constraints (SPPRC) typically solved by a dynamic-programming labeling algorithm. Solving the SPPRC subproblems consumes most of the total BPC computation time. Critical to the performance of the labeling algorithms and thus the BPC algorithm as a whole is the use of effective dominance rules. Classical dominance rules rely on a pairwise comparison of labels and have been used in many labeling algorithms. In contrast, partial dominance describes situations where several labels together are needed to dominate another label, which can then be safely discarded. In this work, we consider SPPRCs, where a linear tradeoff describes the relationship between two resources. We derive a unified partial dominance rule to be used in ad hoc labeling algorithms for solving such SPPRCs as well as insights into its practical implementation. We introduce partial dominance for two important variants of the vehicle routing problem, namely the electric vehicle routing problem with time windows with a partial recharge policy and the split-delivery vehicle routing problem with time windows (SDVRPTW). Computational experiments show the effectiveness of the approach, in particular for the SDVRPTW, leading to an average reduction of 20% of the total BPC computation time, with savings of 30% for the more difficult instances requiring more than 600 s of computation time.

关键词： Branch-price-and-cut Partial dominance Column generation labeling algorithm Vehicle routing and scheduling

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New exact and heuristic algorithms to solve the prize-collecting job sequencing problem with one common and multiple secondary resources

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2023年第1期306卷 65-82页

作者： Froger, Aurelien Sadykov, Ruslan Univ Bordeaux UMR CNRS 5251 F-33405 Talence France Ctr Inria Univ Bordeaux F-33405 Talence France

We study the prize-collecting job sequencing problem with one common and multiple secondary re-sources. In this problem, a set of jobs is given, each with a profit, multiple time windows for its exe-cution, and a duration during which it requires the main resource. Each job also requires a preassigned secondary resource before, during, and after its use of the main resource. The goal is to select and sched-ule the subset of jobs that maximize the total profit. We present a new mixed integer linear programming formulation of the problem and a branch-cut-and-price algorithm as an exact solution method. We also introduce a heuristic algorithm to tackle larger instances. Extensive numerical experiments show that our exact algorithm can solve to optimality literature instances with up to 500 jobs for a particular dataset and up to 250 jobs for another dataset with different characteristics. Our heuristic builds high-quality solutions in a small computational time. It computes new best-known solutions for most of the larger instances.(c) 2022 Elsevier B.V. All rights reserved.

关键词： Scheduling Sequencing labeling algorithm Branch-cut-and-price Iterated local search

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A branch-and-price approach for airport gate assignment problem with chance constraints

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TRANSPORTATION RESEARCH PART B-METHODOLOGICAL 2023年第1期168卷 1-26页

作者： Kim, Junyoung Goo, Byungju Roh, Youngjoo Lee, Chungmok Lee, Kyungsik Seoul Natl Univ Dept Ind Engn Seoul South Korea Hankuk Univ Foreign Studies Dept Ind & Management Engn Seoul South Korea

At an airport, the flights should be attached to the gates to embark or disembark the passengers. The airport gate assignment problem concerns the efficient utilization of gates by assigning flights to the gates according to the flights' planned schedules. However, due to ever-increasing air traffic demands and unpredictable weather conditions, it is hard to expect that the flights strictly follow the planned schedules. Therefore, establishing a robust gate assignment plan against uncertain flight schedule deviations is crucial for airport operators. However, ensuring the robustness of the plan by imposing too long idle times of gates may deteriorate the efficiency of gate usage. To address the trade-off between two goals, we introduce an overlap chance-constrained airport gate assignment problem that limits the probability of an overlap occurrence of flight schedules for each gate to given thresholds while maximizing the sum of preference values of flights for gates. We propose a network-based integer programming model for this problem, estimating the probability distribution using the historical flight arrival/departure deviation data. Then, we strengthen the model using the concept of gate assignment patterns, and a branch-and-price algorithm is devised to solve the model. A labeling algorithm-based efficient column generation algorithm is developed, further accelerated by clustering gates with similar characteristics. Through computational experiments, we demonstrate the efficiency of the proposed algorithm, and the trade-off between the overlap occurrence probability and the preference is analyzed using real-life instances.

关键词： Airport gate assignment Branch-and-price Chance constraints labeling algorithm

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A branch-and-price algorithm for two-echelon electric vehicle routing problem

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COMPLEX & INTELLIGENT SYSTEMS 2023年第3期9卷 2475-2490页

作者： Wu, Zhiguo Zhang, Juliang Beijing Jiaotong Univ Sch Econ & Management Beijing Peoples R China

Motivated by express and e-commerce companies' distribution practices, we study a two-echelon electric vehicle routing problem. In this problem, fuel-powered vehicles are used to transport goods from a depot to intermediate facilities (satellites) in the first echelon, whereas electric vehicles, which have limited driving ranges and need to be recharged at recharging stations, are used to transfer goods from the satellites to customers in the second echelon. We model the problem as an arc flow model and decompose the model into a master problem and pricing subproblem. We propose a branch-and-price algorithm to solve it. We use column generation to solve the restricted master problem to provide lower bounds. By enumerating all the subsets of the satellites, we generate feasible columns by solving the elementary shortest path problem with resource constraints in the first echelon. Then, we design a bidirectional labeling algorithm to generate feasible routes in the second echelon. Comparing the performance of our proposed algorithm with that of CPLEX in solving a set of small-sized instances, we demonstrate the former's effectiveness. We further assess our algorithm in solving two sets of larger scale instances. We also examine the impacts of some model parameters on the solution.

关键词： Two-echelon Electric vehicles Branch-and-price algorithm Column generation labeling algorithm

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A multi-vehicle covering tour problem with speed optimization

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NETWORKS 2022年第2期79卷 119-142页

作者： Margolis, Joshua T. Song, Yongjia Mason, Scott J. Clemson Univ Dept Ind Engn Clemson SC 29634 USA

A multi-vehicle covering tour problem with speed optimization, we aim to construct a set of maximal coverage routes for a fleet of vehicles that serve (observe) a set of secondary sites, given a fixed time schedule and coverage requirements. We develop an exact solution approach using a branch-and-price framework with a label-correcting algorithm and a set of innovative dominance rules to solve the resulting pricing problem. We also develop a two-stage heuristic capable of finding effective initial solutions. In addition, we consider practical extensions to the model by incorporating risk thresholds, energy capacities, and time windows. To validate our proposed solution approaches, we perform an extensive set of numerical experiments. Numerical results show the computational advantage of our proposed solution approaches compared with a state-of-the-art commercial solver.

关键词： branch‐ and‐ price algorithm covering tour labeling algorithm heuristic speed optimization target surveillance vehicle routing

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