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Автор: Grafiati
Опубліковано: 10 грудня 2022
Оновлено: 29 січня 2023

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1

MacLachlan, Jordan, Yi Mei, Juergen Branke, and Mengjie Zhang. "Genetic Programming Hyper-Heuristics with Vehicle Collaboration for Uncertain Capacitated Arc Routing Problems." Evolutionary Computation 28, no. 4 (December 2020): 563–93. http://dx.doi.org/10.1162/evco_a_00267.

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Анотація:
Due to its direct relevance to post-disaster operations, meter reading and civil refuse collection, the Uncertain Capacitated Arc Routing Problem (UCARP) is an important optimisation problem. Stochastic models are critical to study as they more accurately represent the real world than their deterministic counterparts. Although there have been extensive studies in solving routing problems under uncertainty, very few have considered UCARP, and none consider collaboration between vehicles to handle the negative effects of uncertainty. This article proposes a novel Solution Construction Procedure (SCP) that generates solutions to UCARP within a collaborative, multi-vehicle framework. It consists of two types of collaborative activities: one when a vehicle unexpectedly expends capacity ( route failure), and the other during the refill process. Then, we propose a Genetic Programming Hyper-Heuristic (GPHH) algorithm to evolve the routing policy used within the collaborative framework. The experimental studies show that the new heuristic with vehicle collaboration and GP-evolved routing policy significantly outperforms the compared state-of-the-art algorithms on commonly studied test problems. This is shown to be especially true on instances with larger numbers of tasks and vehicles. This clearly shows the advantage of vehicle collaboration in handling the uncertain environment, and the effectiveness of the newly proposed algorithm.
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2

Liu, Yuxin, Yi Mei, Mengjie Zhang, and Zili Zhang. "A Predictive-Reactive Approach with Genetic Programming and Cooperative Coevolution for the Uncertain Capacitated Arc Routing Problem." Evolutionary Computation 28, no. 2 (June 2020): 289–316. http://dx.doi.org/10.1162/evco_a_00256.

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Анотація:
The uncertain capacitated arc routing problem is of great significance for its wide applications in the real world. In the uncertain capacitated arc routing problem, variables such as task demands and travel costs are realised in real time. This may cause the predefined solution to become ineffective and/or infeasible. There are two main challenges in solving this problem. One is to obtain a high-quality and robust baseline task sequence, and the other is to design an effective recourse policy to adjust the baseline task sequence when it becomes infeasible and/or ineffective during the execution. Existing studies typically only tackle one challenge (the other being addressed using a naive strategy). No existing work optimises the baseline task sequence and recourse policy simultaneously. To fill this gap, we propose a novel proactive-reactive approach, which represents a solution as a baseline task sequence and a recourse policy. The two components are optimised under a cooperative coevolution framework, in which the baseline task sequence is evolved by an estimation of distribution algorithm, and the recourse policy is evolved by genetic programming. The experimental results show that the proposed algorithm, called Solution-Policy Coevolver, significantly outperforms the state-of-the-art algorithms to the uncertain capacitated arc routing problem for the ugdb and uval benchmark instances. Through further analysis, we discovered that route failure is not always detrimental. Instead, in certain cases (e.g., when the vehicle is on the way back to the depot) allowing route failure can lead to better solutions.
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3

Liu, Jialin, Ke Tang, and Xin Yao. "Robust Optimization in Uncertain Capacitated Arc Routing Problems: Progresses and Perspectives [Review Article]." IEEE Computational Intelligence Magazine 16, no. 1 (February 2021): 63–82. http://dx.doi.org/10.1109/mci.2020.3039069.

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4

Wang, Juan, Ke Tang, Jose A. Lozano, and Xin Yao. "Estimation of the Distribution Algorithm With a Stochastic Local Search for Uncertain Capacitated Arc Routing Problems." IEEE Transactions on Evolutionary Computation 20, no. 1 (February 2016): 96–109. http://dx.doi.org/10.1109/tevc.2015.2428616.

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5

Babaee Tirkolaee, Erfan, Iraj Mahdavi, Mir Mehdi Seyyed Esfahani, and Gerhard-Wilhelm Weber. "A hybrid augmented ant colony optimization for the multi-trip capacitated arc routing problem under fuzzy demands for urban solid waste management." Waste Management & Research 38, no. 2 (August 13, 2019): 156–72. http://dx.doi.org/10.1177/0734242x19865782.

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Анотація:
Nowadays, urban solid waste management is one of the most crucial activities in municipalities and their affiliated organizations. It includes the processes of collection, transportation and disposal. These major operations require a large amount of resources and investments, which will always be subject to limitations. In this paper, a chance-constrained programming model based on fuzzy credibility theory is proposed for the multi-trip capacitated arc routing problem to cope with the uncertain nature of waste amount generated in urban areas with the aim of total cost minimization. To deal with the complexity of the problem and solve it efficiently, a hybrid augmented ant colony optimization algorithm is developed based on an improved max–min ant system with an innovative probability function and a simulated annealing algorithm. The performance of hybrid augmented ant colony optimization is enhanced by using the Taguchi parameter design method to adjust the parameters’ values optimally. The overall efficiency of the algorithm is evaluated against other similar algorithms using well-known benchmarks. Finally, the applicability of the suggested methodology is tested on a real case study with a sensitivity analysis to evolve the managerial insights and decision aids.
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6

Babaee Tirkolaee, Erfan, Alireza Goli, Maryam Pahlevan, and Ramina Malekalipour Kordestanizadeh. "A robust bi-objective multi-trip periodic capacitated arc routing problem for urban waste collection using a multi-objective invasive weed optimization." Waste Management & Research 37, no. 11 (August 15, 2019): 1089–101. http://dx.doi.org/10.1177/0734242x19865340.

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Анотація:
Urban waste collection is one of the principal processes in municipalities with large expenses and laborious operations. Among the important issues raised in this regard, the lack of awareness of the exact amount of generated waste makes difficulties in the processes of collection, transportation and disposal. To this end, investigating the waste collection issue under uncertainty can play a key role in the decision-making process of managers. This paper addresses a novel robust bi-objective multi-trip periodic capacitated arc routing problem under demand uncertainty to treat the urban waste collection problem. The objectives are to minimize the total cost (i.e. traversing and vehicles’ usage costs) and minimize the longest tour distance of vehicles (makespan). To validate the proposed bi-objective robust model, the ε-constraint method is implemented using the CPLEX solver of GAMS software. Furthermore, a multi-objective invasive weed optimization algorithm is then developed to solve the problem in real-world sizes. The parameters of the multi-objective invasive weed optimization are tuned optimally using the Taguchi design method to enhance its performance. The computational results conducted on different test problems demonstrate that the proposed algorithm can generate high-quality solutions considering three indexes of mean of ideal distance, number of solutions and central processing unit time. It is proved that the ε-constraint method and multi-objective invasive weed optimization can efficiently solve the small- and large-sized problems, respectively. Finally, a sensitivity analysis is performed on one of the main parameters of the problem to study the behavior of the objective functions and provide the optimal policy.
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7

Usberti, Fábio Luiz, Paulo Morelato França, and André Luiz Morelato França. "The open capacitated arc routing problem." Computers & Operations Research 38, no. 11 (November 2011): 1543–55. http://dx.doi.org/10.1016/j.cor.2011.01.012.

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8

Kirlik, Gokhan, and Aydin Sipahioglu. "Capacitated arc routing problem with deadheading demands." Computers & Operations Research 39, no. 10 (October 2012): 2380–94. http://dx.doi.org/10.1016/j.cor.2011.12.008.

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9

Benavent, E., V. Campos, A. Corberan, and E. Mota. "The Capacitated Arc Routing Problem: Lower bounds." Networks 22, no. 7 (December 1992): 669–90. http://dx.doi.org/10.1002/net.3230220706.

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10

Amaya, Alberto, André Langevin, and Martin Trépanier. "The capacitated arc routing problem with refill points." Operations Research Letters 35, no. 1 (January 2007): 45–53. http://dx.doi.org/10.1016/j.orl.2005.12.009.

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11

Martinez, C., I. Loiseau, M. G. C. Resende, and S. Rodriguez. "BRKGA Algorithm for the Capacitated Arc Routing Problem." Electronic Notes in Theoretical Computer Science 281 (December 2011): 69–83. http://dx.doi.org/10.1016/j.entcs.2011.11.026.

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12

Khajepour, Amin, Majid Sheikhmohammady, and Ehsan Nikbakhsh. "Field path planning using capacitated arc routing problem." Computers and Electronics in Agriculture 173 (June 2020): 105401. http://dx.doi.org/10.1016/j.compag.2020.105401.

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13

Chu, Feng, Nacima Labadi, and Christian Prins. "Heuristics for the periodic capacitated arc routing problem." Journal of Intelligent Manufacturing 16, no. 2 (April 2005): 243–51. http://dx.doi.org/10.1007/s10845-004-5892-8.

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14

Riquelme-Rodríguez, Juan-Pablo, Michel Gamache, and André Langevin. "Periodic capacitated arc-routing problem with inventory constraints." Journal of the Operational Research Society 65, no. 12 (December 2014): 1840–52. http://dx.doi.org/10.1057/jors.2013.159.

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15

Pearn, Wen Lea. "Approximate solutions for the capacitated arc routing problem." Computers & Operations Research 16, no. 6 (January 1989): 589–600. http://dx.doi.org/10.1016/0305-0548(89)90044-0.

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16

Archetti, Claudia, Dominique Feillet, Alain Hertz, and M. Grazia Speranza. "The undirected capacitated arc routing problem with profits." Computers & Operations Research 37, no. 11 (November 2010): 1860–69. http://dx.doi.org/10.1016/j.cor.2009.05.005.

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17

Ghiani, Gianpaolo, Gennaro Improta, and Gilbert Laporte. "The capacitated arc routing problem with intermediate facilities." Networks 37, no. 3 (2001): 134–43. http://dx.doi.org/10.1002/net.3.

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18

Mirzaei-Khafri, Soheila, Mahdi Bashiri, Roya Soltani, and Mohammad Khalilzadeh. "A MATHEMATICAL MODEL FOR THE CAPACITATED LOCATION-ARC ROUTING PROBLEM WITH DEADLINES AND HETEROGENEOUS FLEET." Transport 34, no. 6 (September 26, 2019): 692–707. http://dx.doi.org/10.3846/transport.2019.11145.

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Анотація:
This paper considers a Capacitated Location-Arc Routing Problem (CLARP) with Deadlines (CLARPD) and a fleet of capacitated heterogeneous vehicles. The proposed mixed integer programming model determines a subset of potential depots to be opened, the served roads within predefined deadlines, and the vehicles assigned to each open depot. In addition, efficient routing plans are determined to minimize total establishment and traveling costs. Since the CLARP is NP-hard, a Genetic Algorithm (GA) is presented to consider proposed operators, and a constructive heuristic to generate initial solutions. In addition, a Simulated Annealing (SA) algorithm is investigated to compare the performance of the GA. Computational experiments are carried out for several test instances. The computational results show that the proposed GA is promising. Finally, sensitivity analysis confirms that the developed model can meet arc routing timing requirements more precisely compared to the classical Capacitated Arc Routing Problem (CARP).
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19

Wohlk, Sanne. "An Approximation Algorithm for the Capacitated Arc Routing Problem." Open Operational Research Journal 2, no. 1 (October 30, 2008): 8–12. http://dx.doi.org/10.2174/1874243200802010008.

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20

Bensedira, Badis, Abdesslam Layeb, and Zineb Habbas. "Discrete cuckoo search applied to capacitated arc routing problem." International Journal of Metaheuristics 6, no. 1/2 (2017): 37. http://dx.doi.org/10.1504/ijmheur.2017.083096.

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21

Yi Mei, Ke Tang, and Xin Yao. "A Global Repair Operator for Capacitated Arc Routing Problem." IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 39, no. 3 (June 2009): 723–34. http://dx.doi.org/10.1109/tsmcb.2008.2008906.

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22

Yi Mei, Ke Tang, and Xin Yao. "A Memetic Algorithm for Periodic Capacitated Arc Routing Problem." IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 41, no. 6 (December 2011): 1654–67. http://dx.doi.org/10.1109/tsmcb.2011.2158307.

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23

Shang, Ronghua, Hongna Ma, Jia Wang, Licheng Jiao, and Rustam Stolkin. "Immune clonal selection algorithm for capacitated arc routing problem." Soft Computing 20, no. 6 (March 7, 2015): 2177–204. http://dx.doi.org/10.1007/s00500-015-1634-4.

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24

Zbib, Hani, and Gilbert Laporte. "The commodity-split multi-compartment capacitated arc routing problem." Computers & Operations Research 122 (October 2020): 104994. http://dx.doi.org/10.1016/j.cor.2020.104994.

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25

Wøhlk, Sanne. "New lower bound for the Capacitated Arc Routing Problem." Computers & Operations Research 33, no. 12 (December 2006): 3458–72. http://dx.doi.org/10.1016/j.cor.2005.02.015.

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26

Pearn, Wen Lea. "Augment-insert algorithms for the capacitated arc routing problem." Computers & Operations Research 18, no. 2 (January 1991): 189–98. http://dx.doi.org/10.1016/0305-0548(91)90089-a.

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27

Monroy, I. M., C. A. Amaya, and A. Langevin. "The periodic capacitated arc routing problem with irregular services." Discrete Applied Mathematics 161, no. 4-5 (March 2013): 691–701. http://dx.doi.org/10.1016/j.dam.2011.05.014.

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28

Santos, Luís, João Coutinho-Rodrigues, and John R. Current. "An improved heuristic for the capacitated arc routing problem." Computers & Operations Research 36, no. 9 (September 2009): 2632–37. http://dx.doi.org/10.1016/j.cor.2008.11.005.

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29

Gouveia, Luís, Maria Cândida Mourão, and Leonor Santiago Pinto. "Lower bounds for the mixed capacitated arc routing problem." Computers & Operations Research 37, no. 4 (April 2010): 692–99. http://dx.doi.org/10.1016/j.cor.2009.06.018.

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30

Martinelli, Rafael, Marcus Poggi, and Anand Subramanian. "Improved bounds for large scale capacitated arc routing problem." Computers & Operations Research 40, no. 8 (August 2013): 2145–60. http://dx.doi.org/10.1016/j.cor.2013.02.013.

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31

Pearn, Wen Lea. "New lower bounds for the Capacitated Arc Routing Problem." Networks 18, no. 3 (1988): 181–91. http://dx.doi.org/10.1002/net.3230180305.

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32

Wan, Jie, Xinghan Chen, and Ruichang Li. "Improved Memetic Algorithm for Multi-depot Multi-objective Capacitated Arc Routing Problem." MATEC Web of Conferences 308 (2020): 01002. http://dx.doi.org/10.1051/matecconf/202030801002.

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Анотація:
The capacitated arc routing problem (CARP) is a challenging vehicle routing problem with numerous real-world applications. In this paper, an extended version of CARP, the multi-depot multi-objective capacitated arc routing problem (MDMOCARP) is proposed to tackle practical requirements. Firstly, the critical edge decision mechanism and the critical edge random allocation mechanism are proposed to optimize edges between depots. Secondly, a novel adaptive probability of local search with fitness is proposed to improve the Decomposition-Based Memetic Algorithm for Multi-Objective CARP (D-MAENS). Compared with the D-MAENS algorithm, experimental results on MD-CARP instances show that the improved memetic algorithm (IMA) has performed significantly better than D-MAENS on convergence and diversity in the metric IGD and the metric HV.
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33

Kanso, Bilal, Ali Kansou, and Adnan Yassine. "Open Capacitated ARC routing problem by Hybridized Ant Colony Algorithm." RAIRO - Operations Research 55, no. 2 (March 2021): 639–52. http://dx.doi.org/10.1051/ro/2021034.

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Анотація:
The Open Capacitated Arc Routing Problem OCARP is a well-known NP-hard real-world combinatorial optimization problem. It consists of determining optimal routes for vehicles in a given service area at a minimal cost distance. The main real application for OCARP is the Meter Reader Routing Problem (MRRP). In MRRP problem, each worker in the electric (or gas) company must visit and read the electric (or gas) meters to a set of customers by starting his route from the first customer on his visit list and finishing with the last one. The worker leaves where he wants once all the associated customers have been visited. In this paper, a metaheuristic called an Hybridized Ant Colony Algorithm (HACA) is developed and hybridized with a local search algorithm that involves the 2-opt, Swap, Relocate and Cross-exchange moves to solve OCARP problem. Computational results conducted on five different sets of OCARP-instances showed that our proposed algorithm HACA has reached good and competitive results on benchmark instances for the problem.
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34

Saruwatari, Yasufumi, Ryuichi Hirabayashi, and Naonori Nishida. "NODE DUPLICATION LOWER BOUNDS FOR THE CAPACITATED ARC ROUTING PROBLEM." Journal of the Operations Research Society of Japan 35, no. 2 (1992): 119–33. http://dx.doi.org/10.15807/jorsj.35.119.

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35

Hertz, Alain, Gilbert Laporte, and Michel Mittaz. "A Tabu Search Heuristic for the Capacitated arc Routing Problem." Operations Research 48, no. 1 (February 2000): 129–35. http://dx.doi.org/10.1287/opre.48.1.129.12455.

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36

Lining Xing, Philipp Rohlfshagen, Yingwu Chen, and Xin Yao. "An Evolutionary Approach to the Multidepot Capacitated Arc Routing Problem." IEEE Transactions on Evolutionary Computation 14, no. 3 (June 2010): 356–74. http://dx.doi.org/10.1109/tevc.2009.2033578.

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37

Mei, Yi, Ke Tang, and Xin Yao. "Decomposition-Based Memetic Algorithm for Multiobjective Capacitated Arc Routing Problem." IEEE Transactions on Evolutionary Computation 15, no. 2 (April 2011): 151–65. http://dx.doi.org/10.1109/tevc.2010.2051446.

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38

Belenguer, José-Manuel, Enrique Benavent, Nacima Labadi, Christian Prins, and Mohamed Reghioui. "Split-Delivery Capacitated Arc-Routing Problem: Lower Bound and Metaheuristic." Transportation Science 44, no. 2 (May 2010): 206–20. http://dx.doi.org/10.1287/trsc.1090.0305.

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39

Fung, Richard Y. K., Ran Liu, and Zhibin Jiang. "A memetic algorithm for the open capacitated arc routing problem." Transportation Research Part E: Logistics and Transportation Review 50 (February 2013): 53–67. http://dx.doi.org/10.1016/j.tre.2012.11.003.

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40

Chu, Feng, Nacima Labadi, and Christian Prins. "A Scatter Search for the periodic capacitated arc routing problem." European Journal of Operational Research 169, no. 2 (March 2006): 586–605. http://dx.doi.org/10.1016/j.ejor.2004.08.017.

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41

Belenguer, José M., and Enrique Benavent. "A cutting plane algorithm for the capacitated arc routing problem." Computers & Operations Research 30, no. 5 (April 2003): 705–28. http://dx.doi.org/10.1016/s0305-0548(02)00046-1.

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42

Constantino, Miguel, Luís Gouveia, Maria Cândida Mourão, and Ana Catarina Nunes. "The mixed capacitated arc routing problem with non-overlapping routes." European Journal of Operational Research 244, no. 2 (July 2015): 445–56. http://dx.doi.org/10.1016/j.ejor.2015.01.042.

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43

Chen, Yuning, Jin-Kao Hao, and Fred Glover. "A hybrid metaheuristic approach for the capacitated arc routing problem." European Journal of Operational Research 253, no. 1 (August 2016): 25–39. http://dx.doi.org/10.1016/j.ejor.2016.02.015.

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44

Ulusoy, Gündüz. "The fleet size and mix problem for capacitated arc routing." European Journal of Operational Research 22, no. 3 (December 1985): 329–37. http://dx.doi.org/10.1016/0377-2217(85)90252-8.

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45

Arakaki, Rafael Kendy, and Fábio Luiz Usberti. "Hybrid genetic algorithm for the open capacitated arc routing problem." Computers & Operations Research 90 (February 2018): 221–31. http://dx.doi.org/10.1016/j.cor.2017.09.020.

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46

Li, Rui, Xinchao Zhao, Xingquan Zuo, Jianmei Yuan, and Xin Yao. "Memetic algorithm with non-smooth penalty for capacitated arc routing problem." Knowledge-Based Systems 220 (May 2021): 106957. http://dx.doi.org/10.1016/j.knosys.2021.106957.

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47

Ismail. "Implementation Weather-Type Models of Capacitated Arc Routing Problem via Heuristics." American Journal of Applied Sciences 8, no. 4 (April 1, 2011): 382–92. http://dx.doi.org/10.3844/ajassp.2011.382.392.

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48

Xiong, Qian, Jun Peng, Guo Rong Chen, Qi Han, and Jun Yi. "Application of Artificial Immune Algorithm in the Capacitated Arc Routing Problem." Advanced Materials Research 791-793 (September 2013): 1195–98. http://dx.doi.org/10.4028/www.scientific.net/amr.791-793.1195.

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Анотація:
The Capacitated Arc Routing Problem is a typical combinational optimization problem, and traditional optimization methods produced premature convergence problem. Artificial immune algorithm, which simulates biological immune system, is a new intelligent optimization algorithm with good global search capability. This paper proposes AIA to solve the CARP and produces the process and steps for this algorithm. Experiments show that this algorithm can get better solution.
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49

PRAMUDITA, Andie, Eiichi TANIGUCHI, and Ali G. QURESHI. "UNDIRECTED CAPACITATED ARC ROUTING PROBLEM IN DEBRIS COLLECTION OPERATION AFTER DISASTERS." Journal of Japan Society of Civil Engineers, Ser. D3 (Infrastructure Planning and Management) 68, no. 5 (2012): I_805—I_813. http://dx.doi.org/10.2208/jscejipm.68.i_805.

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Kansou, Ali, and Adnan Yassine. "New upper bounds for the multi-depot capacitated arc routing problem." International Journal of Metaheuristics 1, no. 1 (2010): 81. http://dx.doi.org/10.1504/ijmheur.2010.033124.

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