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Статті в журналах з теми "Optimization paths"

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Автор: Grafiati

Опубліковано: 30 травня 2022

Оновлено: 31 травня 2022

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1

Assefa Gebremichail, Aklilu, Cory Beard, and Rahul A. Paropkari. "Multi-Hop Relay Selection Based on Fade Durations." Electronics 9, no. 1 (January 2, 2020): 92. http://dx.doi.org/10.3390/electronics9010092.

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Анотація:

In cooperative relaying, the selection of relays could be based on different parameters. The most well-known and frequently used metric is the signal-to-noise ratio (SNR). In this method of relay selection, the rapid fluctuation of the signal (i.e., fading) is not taken into account in the selection criteria. Such rapid signal change may cause significant loss of information, degrade signal quality for voice or video connections, or could make the channel coding fail. An alternative method of relay selection in a cooperative relay network is by considering fading. Such methods include average fade duration (AFD) and fade duration outage probability (FDOP), which are based on time correlation statistics. Both the AFD and the FDOP are computed in reference to a threshold value for signal quality. This work derives new formulas for two hop and three hop relay paths, with three hop paths given a penalty cost. Then optimization algorithms for each type of relay selection method are derived, including total path and link-by-link optimization. Simulation results provide optimal AFD and FDOP paths for various random network topologies. These paths are then compared to paths that would be found if SNR metrics were used instead. It is shown that SNR optimization results in much different performance. For cases of four sources and four relays, SNR based optimization frequently chose different relay paths, as low as only 63% of the same relay paths as FDOP or AFD optimizations. Because fade duration methods more accurately control the fading nature and true quality of the signals, the results here provide significant improvements in relay performance and allow two and three hop relay paths to be implemented effectively.

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2

KAMIMURA, Masato, Yoshiyuki HATTA, Shuta ITO, Yoshinori KOGA, Toshiaki SAKURAI, and Kunihiro TAKAHASHI. "Structural Optimization and Load Paths." Transactions of the Japan Society of Mechanical Engineers Series A 74, no. 737 (2008): 6–12. http://dx.doi.org/10.1299/kikaia.74.6.

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3

Boissier, M., G. Allaire, and C. Tournier. "Additive manufacturing scanning paths optimization using shape optimization tools." Structural and Multidisciplinary Optimization 61, no. 6 (June 2020): 2437–66. http://dx.doi.org/10.1007/s00158-020-02614-3.

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4

Denkena, Berend, Volker Böß, and Patryk Manuel Hoppe. "Optimization of Non-Cutting Tool Paths." Advanced Materials Research 223 (April 2011): 911–17. http://dx.doi.org/10.4028/www.scientific.net/amr.223.911.

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The focus of CAM systems is on effectively creating cutting tool paths. However, collision risk is very high on multi axes machines when performing non-cutting traverse moves. If available, CAM systems offer limited setting options for non-cutting tool moves. In this paper an approach is presented that allows to automatically generating non-cutting tool paths. Process planners will not only be released from developing and simulating time-consuming multi axes traverse moves. The automatically calculated traverse moves will also machine-specifically optimized with respect to various optimization criteria.

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5

Yan, Fu Yu, Fan Wu, Fei Peng, and Zhi Jie Zhu. "A Survey on Randomized Sampling-Based Path Optimization Methods." Advanced Materials Research 853 (December 2013): 652–60. http://dx.doi.org/10.4028/www.scientific.net/amr.853.652.

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Randomized sampling-based motion planners could efficiently generate collision-free motion paths. However, these paths have some quality problems (with respect to quality measures, such as path length, clearance and smoothness), especially in high dimensional configuration spaces. Thus, researchers studied some path optimization methods to improve path quality and to make paths suitable for practical applications. This paper reviews some of the most influential path optimization methods and gives an overall perspective on the most widely used ideas in the field.

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6

Shi Chunyan, 施春燕, 袁家虎 Yuan Jiahu, 伍凡 Wu Fan, and 万勇建 Wan Yongjian. "Analysis of Polishing Errors by Tool Paths and Optimization of Tool Paths." Acta Optica Sinica 31, no. 8 (2011): 0822003. http://dx.doi.org/10.3788/aos201131.0822003.

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7

Liñán, Roberto José, Iñaki Gaspar, Maria Bordagaray, José Luis Moura, and Angel Ibeas. "Optimization of Cycle Paths with Mathematical Programming." Transportation Research Procedia 3 (2014): 848–55. http://dx.doi.org/10.1016/j.trpro.2014.10.062.

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8

Sheppard, Daniel, Rye Terrell, and Graeme Henkelman. "Optimization methods for finding minimum energy paths." Journal of Chemical Physics 128, no. 13 (April 7, 2008): 134106. http://dx.doi.org/10.1063/1.2841941.

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9

Wigström, Oskar, Nina Sundström, and Bengt Lennartson. "Optimization of Hybrid Systems with Known Paths*." IFAC Proceedings Volumes 45, no. 9 (2012): 39–45. http://dx.doi.org/10.3182/20120606-3-nl-3011.00098.

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10

Tarasyev, Alexandr A., Gavriil A. Agarkov, Camilo A. Ospina Acosta, and Viktor A. Koksharov. "Fuzzy Logic and Optimization of Educational Paths." IFAC-PapersOnLine 51, no. 2 (2018): 511–16. http://dx.doi.org/10.1016/j.ifacol.2018.03.086.

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11

Eriksson, Anders. "Constraint paths in non-linear structural optimization." Computers & Structures 140 (July 2014): 39–47. http://dx.doi.org/10.1016/j.compstruc.2014.05.003.

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12

Hu, Yifan, Yongsheng Ding, and Kuangrong Hao. "An Immune Cooperative Particle Swarm Optimization Algorithm for Fault-Tolerant Routing Optimization in Heterogeneous Wireless Sensor Networks." Mathematical Problems in Engineering 2012 (2012): 1–19. http://dx.doi.org/10.1155/2012/743728.

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The fault-tolerant routing problem is important consideration in the design of heterogeneous wireless sensor networks (H-WSNs) applications, and has recently been attracting growing research interests. In order to maintainkdisjoint communication paths from source sensors to the macronodes, we present a hybrid routing scheme and model, in which multiple paths are calculated and maintained in advance, and alternate paths are created once the previous routing is broken. Then, we propose an immune cooperative particle swarm optimization algorithm (ICPSOA) in the model to provide the fast routing recovery and reconstruct the network topology for path failure in H-WSNs. In the ICPSOA, mutation direction of the particle is determined by multi-swarm evolution equation, and its diversity is improved by immune mechanism, which can enhance the capacity of global search and improve the converging rate of the algorithm. Then we validate this theoretical model with simulation results. The results indicate that the ICPSOA-based fault-tolerant routing protocol outperforms several other protocols due to its capability of fast routing recovery mechanism, reliable communications, and prolonging the lifetime of WSNs.

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13

Lemeshko, Oleksandr, Yurii Hrachov, and Batoul Sleiman. "Research of the Secure Routing Method of Confidential Messages on Disjoint Paths." Problemi telekomunìkacìj, no. 2(27) (December 11, 2020): 43–55. http://dx.doi.org/10.30837/pt.2020.2.04.

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The article proposes a secure routing method of confidential messages in a telecommunication network by disjoint paths and its research results. The presented method of disjoint paths secure routing of confidential messages is based on the sequential solution of two optimization problems: calculating disjoint routes and secure balancing of confidential message fragments on a set of precalculated paths. An optimization model was chosen to determine the set of routes, namely, to calculate the maximum number of disjoint paths, including communication links with minimum compromise probability. Additionally, a model of fragmented transmission using a precalculated set of disjoint paths was selected according to the SPREAD mechanism and Shamir’s scheme to ensure the minimum possible probability of message compromise. The study of the proposed secure routing method on the selected network configuration for three different variants of the link compromise probabilities has been conducted. The study results confirmed the effectiveness of the proposed secure routing method and the efficiency of the underlying optimization models to determine both the set of disjoint paths and the order of secure balancing of confidential message fragments. Prospects for further research in the field of secure routing in telecommunication networks are related to considering the link compromise probabilities and other essential indicators of network security.

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14

Wang, Yong, and Ning Xu. "A Hybrid Particle Swarm Optimization Method for Traveling Salesman Problem." International Journal of Applied Metaheuristic Computing 8, no. 3 (July 2017): 53–65. http://dx.doi.org/10.4018/ijamc.2017070104.

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Traveling salesman problem (TSP) is one well-known NP-Complete problem. The objective is to search the optimal Hamiltonian circuit (OHC) in a tourist map. The particle swarm optimization (PSO) integrated with the four vertices and three lines inequality is introduced to detect the OHC or approximate OHC. The four vertices and three lines inequality is taken as local heuristics to find the local optimal paths composed of four vertices and three lines. Each of this kind of paths in the OHC or approximate OHC conforms to the inequality. The particle swarm optimization is used to search an initial approximation. The four vertices and three lines inequality is applied to convert all the paths in the approximation into the optimal paths. Then a better approximation is obtained. The method is tested with several Euclidean TSP instances. The results show that the much better approximations are searched with the hybrid PSO. The convergence rate is also faster than the traditional PSO under the same preconditions.

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15

Zheng, Yajing, and Wenzhou Jin. "Optimization Method of Locomotive Working Diagram Layout." Journal of Advanced Transportation 2019 (May 2, 2019): 1–9. http://dx.doi.org/10.1155/2019/1315638.

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Rational scheduling of locomotive paths (the locus of the locomotive point in the train working diagram) is an important step in drawing a locomotive working diagram by a computer. But there are some problems in this process, such as the computer usually drawing a locomotive path that overlaps with another locomotive path (in the circumstances, the actual users of the locomotive working diagrams often misread the locomotive planning). At present, there are many studies about assigning sets of locomotives to each train in a preplanned train schedule; in contrast, the studies of visualizing the locomotive planning are relatively rare. Through investigating the locomotive working diagram users, this paper points out that the layout of locomotive paths should put the distance between lines being as large as possible and should put the number of the intersection between lines being as few as possible as the optimization aim which is based to solve the problem of the lines overlap or the problem of the lines beyond the margins for drawing the locomotive paths. This paper also builds the optimization model of locomotive working diagram layout. Based on determining the position of locomotive paths which can be delineated, a genetic algorithm is used to solve the optimizing model of locomotive working diagram layout in this paper. An example of a train working diagram with 36 trains is given at the end of the paper, which indicates that the optimization model of locomotive working diagram layout can better solve the problem of locomotive planning visualization.

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16

Shomali, Nasrin, and Bahman Arasteh. "Mutation reduction in software mutation testing using firefly optimization algorithm." Data Technologies and Applications 54, no. 4 (May 25, 2020): 461–80. http://dx.doi.org/10.1108/dta-08-2019-0140.

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PurposeFor delivering high-quality software applications, proper testing is required. A software test will function successfully if it can find more software faults. The traditional method of assessing the quality and effectiveness of a test suite is mutation testing. One of the main drawbacks of mutation testing is its computational cost. The research problem of this study is the high computational cost of the mutation test. Reducing the time and cost of the mutation test is the main goal of this study.Design/methodology/approachWith regard to the 80–20 rule, 80% of the faults are found in 20% of the fault-prone code of a program. The proposed method statically analyzes the source code of the program to identify the fault-prone locations of the program. Identifying the fault-prone (complex) paths of a program is an NP-hard problem. In the proposed method, a firefly optimization algorithm is used for identifying the most fault-prone paths of a program; then, the mutation operators are injected only on the identified fault-prone instructions.FindingsThe source codes of five traditional benchmark programs were used for evaluating the effectiveness of the proposed method to reduce the mutant number. The proposed method was implemented in Matlab. The mutation injection operations were carried out by MuJava, and the output was investigated. The results confirm that the proposed method considerably reduces the number of mutants, and consequently, the cost of software mutation-test.Originality/valueThe proposed method avoids the mutation of nonfault-prone (simple) codes of the program, and consequently, the number of mutants considerably is reduced. In a program with n branch instructions (if instruction), there are 2n execution paths (test paths) that the data and codes into each of these paths can be considered as a target of mutation. Identifying the error-prone (complex) paths of a program is an NP-hard problem. In the proposed method, a firefly optimization algorithm as a heuristic algorithm is used for identifying the most error-prone paths of a program; then, the mutation operators (faults) are injected only on the identified fault-prone instructions.

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17

Cruz-Chávez, Marco Antonio, Pedro Moreno-Bernal, Rafael Rivera-López, Erika Yesenia Ávila-Melgar, Beatriz Martínez-Bahena, and Martín H. Cruz-Rosales. "GIS Spatial Optimization for Corridor Alignment Using Simulated Annealing." Applied Sciences 10, no. 18 (September 6, 2020): 6190. http://dx.doi.org/10.3390/app10186190.

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Planning corridors for new facilities such as pipeline or transmission lines through geographical spaces is a topographical constraint optimization problem. The corridor planning problem requires finding an optimal route or a set of alternative paths between two locations. This article presents a simulated-annealing-based (SA) approach applying a variable neighborhood strategy in a continuous space to generate competitive and different alternative paths to solve the corridor planning problem. The variable neighborhood method randomly selects two points from a variable interval of the current solution generated by SA creating pseudo-random paths inside a corridor and finding spatially different alternatives. The proposed approach is evaluated with three practical problems using real topographic data from the Veracruz Basin in Mexico. The experimental results show that this approach obtains efficient and competitive solutions with improvements above 18% over those gotten by the compared method.

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18

Behera, Siva Prasad, and Prasanta Kumar Raut. "SOLVING MULTICAST ROUTING PROBLEM USING PARTICLE SWARM OPTIMIZATION." International Journal of Engineering Science Technologies 6, no. 3 (May 26, 2022): 28–34. http://dx.doi.org/10.29121/ijoest.v6.i3.2022.330.

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In a given network there exist many paths from source to destination, among all selected paths finding the optimal shortest path is a challenging task. In this research paper, we proposed a new concept of particle swarm optimization technique, called swarm intelligence, to solve the multicast routing problem to find out the optimal route associated with a network, here we also used triangular fuzzy number tools to encode particles in PSO (particle swarm optimization), first it breaks the network into small spaces and from the small space it computes the optimal path.

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19

Robinson, Y. Harold, and M. Rajaram. "Energy-Aware Multipath Routing Scheme Based on Particle Swarm Optimization in Mobile Ad Hoc Networks." Scientific World Journal 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/284276.

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Mobile ad hoc network (MANET) is a collection of autonomous mobile nodes forming an ad hoc network without fixed infrastructure. Dynamic topology property of MANET may degrade the performance of the network. However, multipath selection is a great challenging task to improve the network lifetime. We proposed an energy-aware multipath routing scheme based on particle swarm optimization (EMPSO) that uses continuous time recurrent neural network (CTRNN) to solve optimization problems. CTRNN finds the optimal loop-free paths to solve link disjoint paths in a MANET. The CTRNN is used as an optimum path selection technique that produces a set of optimal paths between source and destination. In CTRNN, particle swarm optimization (PSO) method is primly used for training the RNN. The proposed scheme uses the reliability measures such as transmission cost, energy factor, and the optimal traffic ratio between source and destination to increase routing performance. In this scheme, optimal loop-free paths can be found using PSO to seek better link quality nodes in route discovery phase. PSO optimizes a problem by iteratively trying to get a better solution with regard to a measure of quality. The proposed scheme discovers multiple loop-free paths by using PSO technique.

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20

Fountas, N. A., C. I. Stergiou, V. D. Majstorović, and N. M. Vaxevanidis. "Intelligent Optimization for Sculptured Surface CNC Tool-paths." Procedia CIRP 55 (2016): 140–45. http://dx.doi.org/10.1016/j.procir.2016.08.033.

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21

Rao, K. Koteswara, Srinivasan Nagaraj, G. Appa Rao, M. Sumender Roy, and Dr GSVP Raju. "Optimization of Decision Paths by using Fuzzy Logic." International Journal of Computer Applications 1, no. 27 (February 25, 2010): 92–97. http://dx.doi.org/10.5120/495-808.

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22

Berclaz, J., F. Fleuret, E. Turetken, and P. Fua. "Multiple Object Tracking Using K-Shortest Paths Optimization." IEEE Transactions on Pattern Analysis and Machine Intelligence 33, no. 9 (September 2011): 1806–19. http://dx.doi.org/10.1109/tpami.2011.21.

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23

Chou, Hsin-Hung, and Christopher J. Marx. "Optimization of Gene Expression through Divergent Mutational Paths." Cell Reports 1, no. 2 (February 2012): 133–40. http://dx.doi.org/10.1016/j.celrep.2011.12.003.

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24

Zhang, Yongcun, and Shutian Liu. "Design of conducting paths based on topology optimization." Heat and Mass Transfer 44, no. 10 (December 19, 2007): 1217–27. http://dx.doi.org/10.1007/s00231-007-0365-1.

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25

Anjos, Miguel F., and Antoine Deza. "Paths, pivots, and practice: the power of optimization." Annals of Operations Research 265, no. 1 (April 9, 2018): 1–4. http://dx.doi.org/10.1007/s10479-018-2853-8.

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26

van der Walle, Peter, Janne Savolainen, L. Kuipers, and Jennifer L. Herek. "Learning from evolutionary optimization by retracing search paths." Chemical Physics Letters 483, no. 1-3 (November 2009): 164–67. http://dx.doi.org/10.1016/j.cplett.2009.10.049.

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27

Sahoo, Rashmi Rekha, and Mitrabinda Ray. "Forest Optimization-Based Test Case Generation for Multiple Paths With Metamorphic Relations." International Journal of Applied Metaheuristic Computing 13, no. 1 (January 2022): 1–18. http://dx.doi.org/10.4018/ijamc.292503.

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In general multiple paths are covered by multiple runs which is a time consuming task. Now a days, metaheuristic techniques are widely used for path coverage. In order to reduce the time, an efficient method is proposed based on Forest Optimization Algorithm (FOA) with Metamorphic Relations (MRs) that cover multiple paths at a time in one run unlike the traditional search based testing. In the proposed approach, initial test case is generated using FOA, the successive test cases are generated using MRs without undergoing several runs. The motive of using FOA is that the searching mechanism of this algorithm having resemblance with the branch / path coverage techniques of testing. To the best of our knowledge, FOA has not been implemented in software testing. The experimental results are compared with three existing work. The efficiency of simply FOA is also shown how it able to cover multiple paths. The results show that FOA with MRs is more efficient in terms of time consumption and number of paths covered.

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28

McCann, Roger C., and P. V. R. Suryanarayana. "Horizontal Well Path Planning and Correction Using Optimization Techniques." Journal of Energy Resources Technology 123, no. 3 (May 11, 2001): 187–93. http://dx.doi.org/10.1115/1.1386390.

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We present a procedure that uses nonlinear optimization theory to plan complex, three-dimensional well paths and path corrections while drilling. The problem of hitting a 3-D target is posed as seeking a profile that optimizes some well-defined objective function (the optimality criterion) subject to equality and inequality constraints. The well path is idealized to contain a finite combination of turn and straight sections. Operational restrictions translate into inequality constraints, and target restrictions translate into equality constraints. Several optimality criteria may be chosen, and appropriate choices are discussed. In this work, we choose optimization with respect to user preferred parameters as the criterion. The resulting nonlinear optimization problem is solved using a sequential gradient-restoration algorithm (SGRA), with scaling and optimal step-size selection. The optimization problem formulation and the solution procedure are described. The procedure is robust, efficient, and clearly superior to trial-and-error heuristic techniques that are commonly used to plan well paths today. A computer program based on this technique has been developed and successfully used. Two examples are included to illustrate the procedure. It is concluded that nonlinear optimization is a powerful and versatile mathematical tool that can be used for planning better, optimal well paths, and can be extended to several other drilling and production problems.

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29

Nanduri, Arun, Ofer M. Shir, Ashley Donovan, Tak-San Ho, and Herschel Rabitz. "Exploring the complexity of quantum control optimization trajectories." Physical Chemistry Chemical Physics 17, no. 1 (2015): 334–47. http://dx.doi.org/10.1039/c4cp03853c.

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30

Shang, Feng Jun, and Zhe Geng. "A MAC-Layer Network Coding Opportunity Optimization Scheme in Multi-Hop Wireless Networks." Applied Mechanics and Materials 529 (June 2014): 721–25. http://dx.doi.org/10.4028/www.scientific.net/amm.529.721.

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Анотація:

In order to improve the performance of multi-hop wireless network, network coding mixes multiple signals in a single channel. A coding scheme proposed previously which is called BEND is a very compelling network coding applications. While it is another way of such programs, but there is still great potential to be developed. This article, based on BEND, expands the width of the potential paths by asking more potential nodes to join so that it increases network throughput and reduces the transmission delay at the same time. It is not a right way neither in theory nor in practical application that increasing the width of the paths unlimitedly by progressive approach. So the best paths width, as well as the network parameters which affecting the paths width is discussed in the final part of this article.

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31

Costa de Oliveira, Leandro, and Tsuzuki Marcos de Sales Guerra. "Optimization of the 2 1/2 D Pocket Machining Using Multiple Tools." Advanced Materials Research 223 (April 2011): 918–27. http://dx.doi.org/10.4028/www.scientific.net/amr.223.918.

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Анотація:

This work presents some contributions for optimization of the 2 ½ D pocket machining. The machining strategy considered is divided in internal machining and corners machining. The internal machining is carried through equidistant paths to the contour (offset) made by using Voronoi’s Diagram and the corner machining follows the same principle. As the Voronoi Diagram is parametric, the spaces between the paths can change. Thus, the best situation of spacing between paths can be determined to optimize the process. By using Dynamic Programming, the best combination of dimensions of the available tools can also be identified to remove the material of the pocket in smaller time.

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32

Rathee, Nisha, and Rajender Singh Chhillar. "Model Driven Approach to Secure Optimized Test Paths for Smart Samsung Pay using Hybrid Genetic Tabu Search Algorithm." International Journal of Information System Modeling and Design 9, no. 1 (January 2018): 77–91. http://dx.doi.org/10.4018/ijismd.2018010104.

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Smart mobile pay applications on smart devices have been considered as the most efficient and secure mode of contactless payment. To safeguard customer credit/ debit card details, testing of mobile pay solutions like Samsung Pay is most important and critical task for testers. Testing of all the test cases is very tedious and a time-consuming task, therefore optimization techniques have been used to identify most optimized test paths. In this article, a hybrid genetic and tabu search optimization (HGTO) algorithm is proposed to secure optimized test paths using activity diagram of the smart Samsung Pay application. The proposed approach has been implemented using C++ language on the case study of the Smart Samsung Pay and an online airline reservation system. The experimental results show that the proposed technique is more effective in automatic generation and optimization of test paths, as compared to a simple genetic algorithm.

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33

Yang, Qingbin, Ruixue Yin, Chaowen Li, and Xuqing Feng. "An optimization model of cutting path and parameters for low cost and carbon emissions in a NC milling process." Journal of Physics: Conference Series 2235, no. 1 (May 1, 2022): 012096. http://dx.doi.org/10.1088/1742-6596/2235/1/012096.

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Abstract Based on the analysis of the carbon emissions and the cost evaluation model for NC milling process, the impact of different tool cutting paths to carbon emissions is compared and analyzed. Taking both carbon emissions and cost of NC milling process as optimization goals, constraints are proposed based on machine parameters and processing quality requirements. The optimization model of cutting paths and parameters for low carbon emissions and cost of NC milling process is built where the spindle speeds, feed per tooth and transverse cutting depth are taken into account as optimization variables. An example is employed to validate the model. First, the cutting path of the tool is determined by experience and the cutting parameters are selected under the lowest carbon emissions and cost target. Secondly, the genetic algorithm is used to optimize the cutting paths based on the optimal cutting parameters.

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34

MOHAMMADZADEH, NASER, MEHDI SEDIGHI, and MORTEZA SAHEB ZAMANI. "GATE LOCATION CHANGING: AN OPTIMIZATION TECHNIQUE FOR QUANTUM CIRCUITS." International Journal of Quantum Information 10, no. 03 (April 2012): 1250037. http://dx.doi.org/10.1142/s0219749912500372.

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During the physical design process, the second process of the quantum circuit design flow, using some optimization techniques after layout generation might be useful to improve the metrics or meet the design constraints. Focusing on this issue, this paper proposes an optimization technique using gate location changing to improve the latency of quantum circuits. The proposed technique uses layout and scheduling information to find critical paths and improve their latency by changing locations of the gates on the critical paths. Experimental results show that the proposed technique decreases the latency of quantum circuits up to 26% for the attempted benchmarks.

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35

Xie, Feng-Jie, Ruo-Chen Feng, and Xue-Yan Zhou. "Research on the Optimization of Cross-Border Logistics Paths of the “Belt and Road” in the Inland Regions." Journal of Advanced Transportation 2022 (January 13, 2022): 1–14. http://dx.doi.org/10.1155/2022/5776334.

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Taking logistics time, logistics cost, and carbon emissions as optimization objectives, air transportation is included in the cross-border logistics paths optimization of multimodal transportation. Considering the scale effect of transportation, a multiobjective optimization model of cross-border logistics paths including road, water, railway, and air is constructed. The problem of cross-border logistics paths along the “Belt and Road” regions for cities in inland is studied via the NSGA-II method. The research results show that Chengdu and Xi’an should bear a large number of cross-border air transportation and be constructed as the national airport-type logistics hub. The foreign destinations of cross-border air transportation are distributed in different regions, mainly in Eastern Europe and Eastern Central Europe. The optimization result shows that if there is a 1-fold increase in logistics cost, the logistics time can reduce by 1.37 folds after the cross-border air transportation joins in the model. Such a result has effectively guided the transition from cross-border water transportation to cross-border air transportation.

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36

Crosson, Elizabeth, Tameem Albash, Itay Hen, and A. P. Young. "De-Signing Hamiltonians for Quantum Adiabatic Optimization." Quantum 4 (September 24, 2020): 334. http://dx.doi.org/10.22331/q-2020-09-24-334.

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Quantum fluctuations driven by non-stoquastic Hamiltonians have been conjectured to be an important and perhaps essential missing ingredient for achieving a quantum advantage with adiabatic optimization. We introduce a transformation that maps every non-stoquastic adiabatic path ending in a classical Hamiltonian to a corresponding stoquastic adiabatic path by appropriately adjusting the phase of each matrix entry in the computational basis. We compare the spectral gaps of these adiabatic paths and find both theoretically and numerically that the paths based on non-stoquastic Hamiltonians have generically smaller spectral gaps between the ground and first excited states, suggesting they are less useful than stoquastic Hamiltonians for quantum adiabatic optimization. These results apply to any adiabatic algorithm which interpolates to a final Hamiltonian that is diagonal in the computational basis.

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Hu, Wenbin, Bo Du, Ye Wu, Huangle Liang, Chao Peng, and Qi Hu. "A HYBRID COLUMN GENERATION ALGORITHM BASED ON METAHEURISTIC OPTIMIZATION." TRANSPORT 31, no. 4 (October 25, 2013): 389–407. http://dx.doi.org/10.3846/16484142.2013.819814.

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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 pathkeeping conditions in the main problem.

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Bhatia, Randeep, Murali Kodialam, and T. V. Lakshman. "Finding disjoint paths with related path costs." Journal of Combinatorial Optimization 12, no. 1-2 (June 27, 2006): 83–96. http://dx.doi.org/10.1007/s10878-006-8906-y.

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39

Jha, Roshni, and Dr Shivnath Ghosh. "Energy Efficient Particle Swarm Optimization Based Multipath Routing in WSN." SMART MOVES JOURNAL IJOSCIENCE 4, no. 10 (October 13, 2018): 5. http://dx.doi.org/10.24113/ijoscience.v4i10.164.

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Wireless Networks includes a larger advantage in today’s communication application like environmental, traffic, military, and health observation. To realize these applications it's necessary to possess a reliable routing protocol. discusses about the working of proposed energy efficient bandwidth aware shortest path routing protocol for multipath routing in wireless sensor network. The proposed algorithm is based for choosing energy efficient shortest path. In routing algorithm, route that have shortest path among multipaths selected by particle swarm optimization algorithm. Among these shortest paths, that path is selected which require minimum route selection parameter. The proposed algorithm uses distance as well as energy of nodes as a parameter to find optimum paths using particle swarm optimization. Among these selected paths, only one optimum path is selected which reduces the energy requirement of the network. According to this work there would be improvement in other parameters also such as end to end delay as well as throughput.

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40

Wong, C. K., and Yi Liu. "Lane-Based Optimization for Macroscopic Network Configuration Designs." Discrete Dynamics in Nature and Society 2017 (2017): 1–18. http://dx.doi.org/10.1155/2017/1257569.

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Lane markings (arrows) at individual intersections serve as interfaces to connect upstream and downstream intersections in signal-controlled networks. Demand flows from origins to destinations may need to pass through a series of intersections. If lane markings are not well established to ban turns at intersections, then paths connecting origin and destination (OD) pairs could be inefficient. Due to indirect connections, road users need to take longer paths to reach their destinations. Conventionally, network configurations are fixed inputs for network analysis. In the present study, concepts of the lane-based designs for individual signalized intersections are extended for signal-controlled network designs. Taking OD demand flows as inputs, the proposed algorithm will optimize all lane markings and assigned lane flows on approach lanes. Paths (flows) will then be optimized by linking up the optimized lane markings across upstream and downstream intersections. Traffic signal settings at individual intersections will be optimized simultaneously by maximizing the reserve capacity for the entire OD demand flow matrix. The problem is formulated as a Binary-Mixed-Integer-Linear-Program (BMILP) and a standard branch-and-bound routine is applied to solve for global optimum solutions. A numerical example using a 4-intersection network will be given to demonstrate the effectiveness of the proposed design methodology.

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41

Kovács, Gergely, Benedek Nagy, Gergely Stomfai, Neşet Deniz Turgay, and Béla Vizvári. "Discrete Optimization: The Case of Generalized BCC Lattice." Mathematics 9, no. 3 (January 20, 2021): 208. http://dx.doi.org/10.3390/math9030208.

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Recently, operations research, especially linear integer-programming, is used in various grids to find optimal paths and, based on that, digital distance. The 4 and higher-dimensional body-centered-cubic grids is the nD (n≥4) equivalent of the 3D body-centered cubic grid, a well-known grid from solid state physics. These grids consist of integer points such that the parity of all coordinates are the same: either all coordinates are odd or even. A popular type digital distance, the chamfer distance, is used which is based on chamfer paths. There are two types of neighbors (closest same parity and closest different parity point-pairs), and the two weights for the steps between the neighbors are fixed. Finding the minimal path between two points is equivalent to an integer-programming problem. First, we solve its linear programming relaxation. The optimal path is found if this solution is integer-valued. Otherwise, the Gomory-cut is applied to obtain the integer-programming optimum. Using the special properties of the optimization problem, an optimal solution is determined for all cases of positive weights. The geometry of the paths are described by the Hilbert basis of the non-negative part of the kernel space of matrix of steps.

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Catania, Rick, Abdalla Diraz, Dominic Maier, Armani Tagle, and Pınar Acar. "Mathematical Strategies for Design Optimization of Multiphase Materials." Mathematical Problems in Engineering 2019 (March 12, 2019): 1–10. http://dx.doi.org/10.1155/2019/4024637.

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This work addresses various mathematical solution strategies adapted for design optimization of multiphase materials. The goal is to improve the structural performance by optimizing the distribution of multiple phases that constitute the material. Examples include the optimization of multiphase materials and composites with spatially varying fiber paths using a finite element analysis scheme. In the first application, the phase distribution of a two-phase material is optimized to improve the structural performance. A radial basis function (RBF) based machine learning algorithm is utilized to perform a computationally efficient design optimization and it is found to provide equivalent results with the physical model. The second application concentrates on the optimization of spatially varying fiber paths of a composite material. The fiber paths are described by the Non-Uniform Rational Bezier (B)-Spline Surface (NURBS) using a bidirectional control point representation including 25 parameters. The optimum fiber path is obtained for various loading configurations by optimizing the NURBS parameters that control the overall distribution of fibers. Next, a direct sensitivity analysis is conducted to choose the critical set of parameters from the design point to improve the computational time efficiency. The optimized fiber path obtained with the reduced number of NURBS parameters is found to provide similar structural properties compared to the optimized fiber path that is modeled with a full NURBS representation with 25 parameters.

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Diehl, Joscha, Peter K. Friz, and Paul Gassiat. "Stochastic control with rough paths." Applied Mathematics & Optimization 75, no. 2 (February 11, 2016): 285–315. http://dx.doi.org/10.1007/s00245-016-9333-9.

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Fl�m, Sjur Didrik. "Paths to constrained Nash equilibria." Applied Mathematics & Optimization 27, no. 3 (May 1993): 275–89. http://dx.doi.org/10.1007/bf01314819.

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45

Rafsanjani, Marjan Kuchaki, Hamideh Fatemidokht, and Valentina Emilia Balas. "Modeling and optimization of Quality of Service routing in Mobile Ad hoc Networks." Open Physics 14, no. 1 (January 1, 2016): 498–507. http://dx.doi.org/10.1515/phys-2016-0058.

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AbstractMobile ad hoc networks (MANETs) are a group of mobile nodes that are connected without using a fixed infrastructure. In these networks, nodes communicate with each other by forming a single-hop or multi-hop network. To design effective mobile ad hoc networks, it is important to evaluate the performance of multi-hop paths. In this paper, we present a mathematical model for a routing protocol under energy consumption and packet delivery ratio of multi-hop paths. In this model, we use geometric random graphs rather than random graphs. Our proposed model finds effective paths that minimize the energy consumption and maximizes the packet delivery ratio of the network. Validation of the mathematical model is performed through simulation.

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46

Paul, Raphael, and Karl Heinz Hoffmann. "Cyclic Control Optimization Algorithm for Stirling Engines." Symmetry 13, no. 5 (May 13, 2021): 873. http://dx.doi.org/10.3390/sym13050873.

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The ideal Stirling cycle describes a specific way to operate an equilibrium Stirling engine. This cycle consists of two isothermal and two isochoric strokes. For non-equilibrium Stirling engines, which may feature various irreversibilities and whose dynamics is characterized by a set of coupled ordinary differential equations, a control strategy that is based on the ideal cycle will not necessarily yield the best performance—for example, it will not generally lead to maximum power. In this paper, we present a method to optimize the engine’s piston paths for different objectives; in particular, power and efficiency. Here, the focus is on an indirect iterative gradient algorithm that we use to solve the cyclic optimal control problem. The cyclic optimal control problem leads to a Hamiltonian system that features a symmetry between its state and costate subproblems. The symmetry manifests itself in the existence of mutually related attractive and repulsive limit cycles. Our algorithm exploits these limit cycles to solve the state and costate problems with periodic boundary conditions. A description of the algorithm is provided and it is explained how the control can be embedded in the system dynamics. Moreover, the optimization results obtained for an exemplary Stirling engine model are discussed. For this Stirling engine model, a comparison of the optimized piston paths against harmonic piston paths shows significant gains in both power and efficiency. At the maximum power point, the relative power gain due to the power-optimal control is ca. 28%, whereas the relative efficiency gain due to the efficiency-optimal control at the maximum efficiency point is ca. 10%.

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Kempes, Christopher P., and David C. Krakauer. "The Multiple Paths to Multiple Life." Journal of Molecular Evolution 89, no. 7 (July 12, 2021): 415–26. http://dx.doi.org/10.1007/s00239-021-10016-2.

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AbstractWe argue for multiple forms of life realized through multiple different historical pathways. From this perspective, there have been multiple origins of life on Earth—life is not a universal homology. By broadening the class of originations, we significantly expand the data set for searching for life. Through a computational analogy, the origin of life describes both the origin of hardware (physical substrate) and software (evolved function). Like all information-processing systems, adaptive systems possess a nested hierarchy of levels, a level of function optimization (e.g., fitness maximization), a level of constraints (e.g., energy requirements), and a level of materials (e.g., DNA or RNA genome and cells). The functions essential to life are realized by different substrates with different efficiencies. The functional level allows us to identify multiple origins of life by searching for key principles of optimization in different material form, including the prebiotic origin of proto-cells, the emergence of culture, economic, and legal institutions, and the reproduction of software agents.

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Yan, Fu Yu, Fan Wu, Fei Peng, and Zhi Jie Zhu. "A Path Clearance Optimization Method Based on Retraction Algorithm for Motion Planning." Applied Mechanics and Materials 687-691 (November 2014): 1241–44. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.1241.

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The retraction algorithm could make the whole path lie on the medial axis in 2D environment. However, it limits the initial and goal configuration lie on the medial axis. Therefore the paper proposed a path clearance optimization method to deal with the problem. The method retracted configurations of the original path to the medial axis. Then it added the retracted configurations, the initial and goal configuration to the retracted path. We apply R-retraction algorithm to the local paths, but not to the local paths between the initial, goal configuration and their retracted configurations. Finally, we proposed a method to remove the branches. We validated the algorithm in virtual environment. The experiments showed that the optimization method could make the whole retracted path lie on the medial axis and the start and goal configuration lie on any free space. Also the proposed method can get paths with maximum clearance in 2D environment in real-time.

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Huang, Wen Wei, Gang Yao, Xiao Yan Qiu, Nian Liu, and Guang Tang Chen. "Optimization of Restoration Paths of Power System after Blackout." Applied Mechanics and Materials 347-350 (August 2013): 1467–72. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.1467.

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Optimization of restoration paths of power system after blackout is a multi-stage, multi-target, multi-variable combinatorial problem in the power system restoration. This paper presents a reasonable model and effectually method. The proposed model is considered as a typical partial minimum spanning tree problem from the mathematical point of view which considering all kinds of constraints. Improved data envelopment analysis (DEA) was used to get the weight which considering line charging reactive power, weather conditions, operation time and betweenness of transmission lines. The improved genetic algorithm method is employed to solve this problem. Finally, an example is given which proves the strategy of the line restoration can effectively handle the uncertainty of the system recovery process, to guarantee the system successfully restored after the catastrophic accidents.

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Vaucher, Alain C., and Markus Reiher. "Minimum Energy Paths and Transition States by Curve Optimization." Journal of Chemical Theory and Computation 14, no. 6 (April 12, 2018): 3091–99. http://dx.doi.org/10.1021/acs.jctc.8b00169.

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