Knowledge (XXG)

Rider optimization algorithm

Source đź“ť

79:
follower employs multidirectional search space considering leading rider, which is useful for algorithm as it improves convergence rate. The overtaker undergoes its own position to attain target considering nearby locations of leader. The benefit of overtaker is that it facilitates faster convergence with huge global neighbourhood. As per ROA, the global optimal convergence is function of overtaker, whose position relies on the position of the leader, success rate, and directional indicator. The attacker adapts position of leader to accomplish destination by using its utmost speed. Moreover, it is responsible for initializing the multidirectional search using fast search for accelerating search speed.
3145: 75:(ROA) is devised based on a novel computing method, namely fictional computing that undergoes series of process to solve the issues of optimizations using imaginary facts and notions. ROA relies on the groups of rider that struggle to reach the target. ROA employs rider groups that take a trip to reach common target in order to become winner. In ROA, the count of groups is four wherein equal riders are placed. 83:
the prescribed method using current success rate. The leader is defined using the success rate at current instance. The process is repeated till the riders go into off time that is maximal instant provided to riders to attain intended location. After reaching off time, the rider at leading position is termed winner.
82:
Despite the riders undergoes a specific method, the major factors employed for reaching the target are correct riding of vehicles and proper management of accelerator, steering, brake and gear. At each time instance, the riders alter its position towards target by regulating these factors and follow
2314:
The applications of ROA are noticed in several domains that involve: Engineering Design Optimization Problems, Diabetic retinopathy detection, Document clustering, Plant disease detection, Attack Detection, Enhanced Video Super Resolution, Clustering, Webpages Re-ranking, Task scheduling, Medical
78:
The four groups adapted in ROA are attacker, overtaker, follower, and bypass rider. Each group undergoes series of strategy to attain the target. The goal of bypass rider is to attain target by bypassing leader's path. The follower tries to follow the position of leader in axis. Furthermore, the
859:
The position of rider in each group is updated to discover rider at leading position and hence is winner. Thus, the rider update the position using the features of each rider defined on the definition. The update position of each rider is explained below:
646:
After rider group parameters initialization, the rate of success considering each rider is evaluated. The rate of success is computed with distance and is measured between rider location and target and is formulated as,
1648: 219: 741: 1829: 1474: 1409: 1038: 1983:
The parameter of rider's update is important to discover an effective solution. Moreover, the steering angle, gears are updated with activity counter, and are updated with success rate.
3042: 2564:
Jadhav AS., Patil PB. and Biradar S (2020). "Optimal feature selection-based diabetic retinopathy detection using improved rider optimization algorithm enabled with deep learning".
623: 1159: 1251: 2180: 2913: 851:
The rate of success is employed as significant part in discovering leader. The rider that reside in near target location is supposed to contain highest rate of success.
297: 2631: 1865: 445: 3037: 2022: 1965: 2217: 1219: 1189: 814: 387: 357: 327: 2305: 2274: 2132: 2062: 1885: 1101: 841: 784: 1925: 2102: 2082: 1945: 1905: 1121: 1074: 561: 541: 521: 501: 481: 255: 117: 2662: 3051: 3531: 843:
indicate target position. To elevate rate of success, distance must be minimized and hence, distance reciprocal offers the success rate of rider.
2906: 2821: 1487: 863:
The follower has an inclination to update position based on location of leading rider to attain target in quick manner and is expressed as,
2804:
Sreenivasulu P and Varadharajan S (2020). "Algorithmic Analysis on Medical Image Compression Using Improved Rider Optimization Algorithm".
2845:
Vhatkar KN and Bhole GP (2020). "Improved rider optimization for optimal container resource allocation in cloud with security assurance".
2344:
Binu D and Kariyappa BS (2019). "RideNN: A new rider optimization algorithm based neural network for fault diagnosis of analog circuits".
3612: 3074: 3126: 2987: 1479:
The attacker contains an inclination to confiscate the leaders position by following the leader's update process and is expressed as,
127: 3094: 91:
The ROA is motivated from riders, who contend to reach anticipated location. The steps employed in ROA algorithm are defined below:
2738:
Sankpal LJ and Patil SH (2020). "Rider-Rank Algorithm-Based Feature Extraction for Re-ranking the Webpages in the Search Engine".
3205: 2899: 2660:
Jagdale RH and Shah SK (2020). "Modified Rider Optimization-based V Channel Magnification for Enhanced Video Super Resolution".
1256:
The overtaker's update position is utilized to elevate rate of success by discovering overtaker position and is represented as,
2480:
Binu D and Kariyappa BS (2020). "Rider Deep LSTM Network for Hybrid Distance Score-based Fault Prediction in Analog Circuits".
3482: 3144: 3590: 3210: 2406: 655: 3526: 3494: 2442:
Binu D and Kariyappa BS (2020). "Multi-Rider Optimization-based Neural Network for Fault Isolation in Analog Circuits".
3575: 3200: 3521: 3477: 3079: 1674: 3370: 3099: 119:, and initializations of its positions are performed in arbitrary manner. The initialization of group is given by, 3260: 1430: 1264: 871: 2922: 3445: 3307: 2249:) Select the rider with high success rate Update rider parameters Return 99:
The foremost step is the initialization of algorithm which is done using four groups of riders represented as
3633: 3489: 3388: 3104: 2982: 3580: 3565: 3455: 3333: 2959: 2926: 2134:
Initialize solution set Initialize other parameter of rider. Find rate of success using equation (
571: 2880:
Augustine S and Ananth JP (2020). "A modified rider optimization algorithm for multihop routing in WSN".
3469: 3435: 3338: 3280: 3161: 2967: 2947: 2625: 1126: 1224: 563:
signifies rag bull rider. Hence, the relation amongst the aforementioned attributes is represented as,
3516: 3343: 3255: 2528: 2353: 2891: 2766: 2647:
In Proceedings of 4th International Conference on Intelligent Computing and Control Systems (ICICCS)
3585: 3450: 3403: 3393: 3245: 3233: 3046: 3029: 2934: 2425: 1666:
Here, the update rule of bypass riders is exhibited wherein standard bypass rider is expressed as,
2645:
Sarma, S.K (2020). "Rider Optimization based Optimized Deep-CNN towards Attack Detection in IoT".
2581:"Frequent itemset-based feature selection and Rider Moth Search Algorithm for document clustering" 2146: 3320: 3289: 3275: 3265: 3056: 2862: 2827: 2786: 2720: 2679: 2546: 2497: 2459: 2369: 2024:
wherein, leader is discovered. After race completion, the leading rider is considered as winner.
2972: 260: 3328: 3006: 2817: 1850: 1994: 1950: 400: 3408: 3398: 3302: 3179: 3084: 3066: 3019: 2930: 2854: 2809: 2778: 2747: 2710: 2671: 2592: 2536: 2489: 2451: 2361: 2316: 2187: 1194: 1164: 789: 362: 332: 302: 2278: 2252: 2110: 2040: 1975:
After executing process of update, the rate of success considering each rider is computed.
1870: 1079: 819: 762: 3424: 1910: 392:
The count of riders is evaluated with count of riders of each group and is expressed as,
2532: 2517:"An Improved Rider Optimization Algorithm for solving Engineering Optimization Problems" 2357: 3412: 3297: 3184: 3118: 3089: 2087: 2067: 1930: 1890: 1106: 1059: 546: 526: 506: 486: 466: 240: 102: 3627: 3570: 3554: 2882:
International Journal of Numerical Modelling: Electronic Networks, Devices and Fields
2866: 2831: 2790: 2724: 2683: 2614:"Deep neural network based Rider-Cuckoo Search Algorithm for plant disease detection" 2613: 2550: 2501: 2463: 2808:. Lecture Notes in Networks and Systems. Vol. 103. Springer. pp. 267–274. 2767:"Fitness rate-based rider optimization enabled for optimal task scheduling in cloud" 2373: 3508: 3014: 2782: 2813: 2699:"Optimal cluster head selection using modified rider assisted clustering for IoT" 2597: 2580: 3595: 2977: 2541: 2516: 2858: 2715: 2698: 2675: 2455: 2751: 2493: 2365: 2997: 3317: 1643:{\displaystyle S_{l+1}^{a}(v,\rho )=S^{G}(G,\rho )++\partial _{v}^{l}} 2243:) Rank the riders based on success rate using equation ( 2585:
Journal of King Saud University-Computer and Information Sciences
214:{\displaystyle S_{l}=\{S_{l}(v,k)\};1\leq v\leq P,1\leq k\leq W} 3552: 3368: 3231: 3159: 2945: 2895: 2847:
International Journal of Pervasive Computing and Communications
2387: 2237:) Update position of bypass rider with equation ( 3143: 2225:) Update position of overtaker with equation ( 2231:) Update position of attacker with equation ( 95:
Initialization of Rider and other algorithmic parameters
2612:
Cristin R., Kumar BS., Priya C and Karthick K (2020).
2346:
IEEE Transactions on Instrumentation & Measurement
658: 574: 403: 2281: 2255: 2190: 2149: 2113: 2090: 2070: 2043: 1997: 1953: 1933: 1913: 1893: 1873: 1853: 1677: 1490: 1433: 1267: 1227: 1197: 1167: 1129: 1109: 1082: 1062: 874: 822: 792: 765: 736:{\textstyle Successrate={\frac {1}{\|S_{v}-l_{t}\|}}} 549: 529: 509: 489: 469: 365: 335: 305: 263: 243: 130: 105: 3507: 3468: 3434: 3423: 3381: 3316: 3288: 3274: 3244: 3193: 3172: 3117: 3065: 3028: 3005: 2996: 2958: 61: 53: 45: 37: 29: 21: 2771:Information Security Journal: A Global Perspective 2299: 2268: 2211: 2174: 2126: 2096: 2076: 2056: 2016: 1959: 1939: 1919: 1899: 1879: 1859: 1823: 1642: 1468: 1403: 1245: 1213: 1183: 1153: 1115: 1095: 1068: 1032: 835: 808: 778: 735: 617: 555: 535: 515: 495: 475: 439: 381: 351: 321: 291: 249: 213: 111: 2579:Yarlagadda M., Rao KG. and Srikrishna A (2019). 2806:Innovations in Computer Science and Engineering 1927:indicate a random number ranging between 1 and 1824:{\displaystyle S_{l+1}^{b}(v,\rho )=\lambda ]} 2907: 1461: 1451: 1365: 1355: 8: 2630:: CS1 maint: multiple names: authors list ( 2315:Image Compression, Resource allocation, and 2219:Update position of follower using equation ( 1469:{\displaystyle D_{l}^{*}{\bigl (}v{\bigr )}} 1404:{\displaystyle S_{l+1}^{o}(v,o)=S_{l}(v,o)+} 1033:{\displaystyle S_{l+1}^{f}(v,o)=S^{G}(G,o)+} 727: 701: 172: 144: 16: 2663:International Journal of Image and Graphics 2482:IEEE Transactions on Industrial Electronics 3549: 3465: 3431: 3378: 3365: 3285: 3241: 3228: 3169: 3156: 3002: 2955: 2942: 2914: 2900: 2892: 2444:Journal of Circuits, Systems and Computers 1991:The procedure is iterated repeatedly till 2714: 2596: 2540: 2280: 2260: 2254: 2189: 2160: 2148: 2118: 2112: 2089: 2069: 2048: 2042: 2002: 1996: 1967:represent random number between 0 and 1. 1952: 1932: 1912: 1892: 1872: 1852: 1770: 1727: 1693: 1682: 1676: 1634: 1629: 1598: 1585: 1574: 1534: 1506: 1495: 1489: 1460: 1459: 1450: 1449: 1443: 1438: 1432: 1377: 1364: 1363: 1354: 1353: 1347: 1342: 1311: 1283: 1272: 1266: 1237: 1232: 1226: 1202: 1196: 1172: 1166: 1145: 1134: 1128: 1108: 1087: 1081: 1061: 1018: 1013: 985: 972: 961: 918: 890: 879: 873: 827: 821: 797: 791: 770: 764: 721: 708: 695: 657: 605: 573: 548: 528: 508: 488: 468: 402: 370: 364: 340: 334: 310: 304: 268: 262: 242: 151: 135: 129: 104: 3148:Optimization computes maxima and minima. 1161:signifies angle of steering considering 2327: 2623: 1887:symbolize random number between 1 and 15: 3344:Principal pivoting algorithm of Lemke 618:{\textstyle B+J+O+A+K={\frac {P}{5}}} 7: 2475: 2473: 2437: 2435: 2339: 2337: 2335: 2333: 2331: 1668: 1481: 1258: 865: 855:Evaluate the rider’s update position 649: 565: 394: 121: 2515:Wang G., Yuan Y. and Guo W (2019). 2988:Successive parabolic interpolation 2697:Poluru RK and Ramasamy LK (2020). 1626: 1229: 1154:{\displaystyle \varphi _{v,o}^{l}} 1103:represent leading rider position, 1010: 17:Rider Optimization Algorithm (ROA) 14: 3308:Projective algorithm of Karmarkar 1246:{\displaystyle \partial _{v}^{l}} 3303:Ellipsoid algorithm of Khachiyan 3206:Sequential quadratic programming 3043:Broyden–Fletcher–Goldfarb–Shanno 2084:, maximum iteration 1476:signifies direction indicator. 1076:signifies coordinate selector, 257:signifies count of riders, and 3261:Reduced gradient (Frank–Wolfe) 2765:Alameen A and Gupta A (2020). 2618:Artificial Intelligence Review 2407:"Rider Optimization Algorithm" 1818: 1815: 1812: 1806: 1794: 1788: 1776: 1760: 1754: 1745: 1733: 1720: 1711: 1699: 1619: 1616: 1604: 1558: 1552: 1540: 1524: 1512: 1398: 1395: 1383: 1335: 1329: 1317: 1301: 1289: 1027: 1024: 1003: 991: 954: 942: 936: 924: 908: 896: 847:Determination of leading rider 286: 274: 169: 157: 1: 3591:Spiral optimization algorithm 3211:Successive linear programming 2783:10.1080/19393555.2020.1769780 3329:Simplex algorithm of Dantzig 3201:Augmented Lagrangian methods 2814:10.1007/978-981-15-2043-3_32 2598:10.1016/j.jksuci.2019.09.002 2175:{\displaystyle l<L_{OFF}} 73:rider optimization algorithm 2542:10.1109/ACCESS.2019.2923468 2245: 2239: 2233: 2227: 2221: 2136: 3650: 2859:10.1108/IJPCC-12-2019-0094 1867:signifies random number, 292:{\displaystyle S_{l}(v,k)} 3608: 3561: 3548: 3532:Push–relabel maximum flow 3377: 3364: 3334:Revised simplex algorithm 3240: 3227: 3168: 3155: 3141: 2954: 2941: 2716:10.1049/iet-com.2020.0236 2676:10.1142/S0219467821500030 2566:Evolutionary Intelligence 2456:10.1142/S0218126621500481 2405:Binu, D (24 March 2019). 2037:Arbitrary rider position 1979:Update of Rider parameter 1123:indicate leader's index, 3057:Symmetric rank-one (SR1) 3038:Berndt–Hall–Hall–Hausman 2494:10.1109/TIE.2020.3028796 2366:10.1109/TIM.2018.2836058 1860:{\displaystyle \lambda } 543:represent attacker, and 483:signifies bypass rider, 440:{\textstyle P=B+J+O+A+K} 3581:Parallel metaheuristics 3389:Approximation algorithm 3100:Powell's dog leg method 3052:Davidon–Fletcher–Powell 2948:Unconstrained nonlinear 2064:, iteration 2017:{\displaystyle L_{OFF}} 1960:{\displaystyle \delta } 642:Finding rate of success 3566:Evolutionary algorithm 3149: 2752:10.1093/comjnl/bxaa032 2301: 2270: 2213: 2212:{\displaystyle v=1toP} 2176: 2128: 2098: 2078: 2058: 2018: 1961: 1941: 1921: 1901: 1881: 1861: 1825: 1644: 1470: 1405: 1247: 1215: 1214:{\displaystyle o^{th}} 1185: 1184:{\displaystyle v^{th}} 1155: 1117: 1097: 1070: 1034: 837: 810: 809:{\displaystyle v^{th}} 786:symbolize position of 780: 737: 619: 557: 537: 517: 497: 477: 441: 383: 382:{\displaystyle l^{th}} 353: 352:{\displaystyle k^{th}} 323: 322:{\displaystyle v^{th}} 299:signifies position of 293: 251: 215: 113: 3339:Criss-cross algorithm 3162:Constrained nonlinear 3147: 2968:Golden-section search 2302: 2300:{\displaystyle l=l+1} 2271: 2269:{\displaystyle S^{G}} 2214: 2177: 2129: 2127:{\displaystyle S^{G}} 2099: 2079: 2059: 2057:{\displaystyle S_{l}} 2019: 1962: 1942: 1922: 1902: 1882: 1880:{\displaystyle \chi } 1862: 1826: 1645: 1471: 1406: 1248: 1216: 1186: 1156: 1118: 1098: 1096:{\displaystyle S^{G}} 1071: 1035: 838: 836:{\displaystyle l_{t}} 811: 781: 779:{\displaystyle S_{v}} 738: 620: 558: 538: 523:signifies overtaker, 518: 498: 478: 442: 384: 354: 324: 294: 252: 216: 114: 3256:Cutting-plane method 2740:The Computer Journal 2279: 2253: 2188: 2147: 2111: 2088: 2068: 2041: 1995: 1971:Finding success rate 1951: 1931: 1920:{\displaystyle \xi } 1911: 1891: 1871: 1851: 1675: 1488: 1431: 1265: 1253:represent distance. 1225: 1195: 1165: 1127: 1107: 1080: 1060: 872: 820: 790: 763: 656: 572: 547: 527: 507: 503:represent follower, 487: 467: 401: 363: 333: 303: 261: 241: 128: 103: 3586:Simulated annealing 3404:Integer programming 3394:Dynamic programming 3234:Convex optimization 3095:Levenberg–Marquardt 2533:2019IEEEA...780570W 2358:2019ITIM...68....2B 2030:rider-optimization 1698: 1639: 1590: 1511: 1448: 1352: 1288: 1242: 1150: 1023: 977: 895: 38:Year of development 18: 3266:Subgradient method 3150: 3075:Conjugate gradient 2983:Nelder–Mead method 2703:IET Communications 2297: 2266: 2209: 2172: 2124: 2094: 2074: 2054: 2014: 1957: 1937: 1917: 1897: 1877: 1857: 1821: 1678: 1640: 1625: 1570: 1491: 1466: 1434: 1401: 1338: 1268: 1243: 1228: 1211: 1181: 1151: 1130: 1113: 1093: 1066: 1030: 1009: 957: 875: 833: 806: 776: 733: 615: 553: 533: 513: 493: 473: 437: 379: 349: 319: 289: 247: 211: 109: 3621: 3620: 3604: 3603: 3544: 3543: 3540: 3539: 3503: 3502: 3464: 3463: 3360: 3359: 3356: 3355: 3352: 3351: 3223: 3222: 3219: 3218: 3139: 3138: 3135: 3134: 3113: 3112: 2823:978-981-15-2042-6 2746:(10): 1479–1489. 2709:(13): 2189–2201. 2097:{\displaystyle L} 2077:{\displaystyle l} 1987:Off time of rider 1940:{\displaystyle P} 1900:{\displaystyle P} 1845: 1844: 1664: 1663: 1425: 1424: 1116:{\displaystyle G} 1069:{\displaystyle o} 1054: 1053: 757: 756: 731: 639: 638: 613: 556:{\displaystyle K} 536:{\displaystyle A} 516:{\displaystyle O} 496:{\displaystyle J} 476:{\displaystyle B} 461: 460: 250:{\displaystyle P} 235: 234: 112:{\displaystyle V} 69: 68: 3641: 3550: 3466: 3432: 3409:Branch and bound 3399:Greedy algorithm 3379: 3366: 3286: 3242: 3229: 3170: 3157: 3105:Truncated Newton 3020:Wolfe conditions 3003: 2956: 2943: 2916: 2909: 2902: 2893: 2886: 2885: 2877: 2871: 2870: 2842: 2836: 2835: 2801: 2795: 2794: 2762: 2756: 2755: 2735: 2729: 2728: 2718: 2694: 2688: 2687: 2657: 2651: 2650: 2642: 2636: 2635: 2629: 2621: 2609: 2603: 2602: 2600: 2591:(4): 1098–1109. 2576: 2570: 2569: 2561: 2555: 2554: 2544: 2512: 2506: 2505: 2477: 2468: 2467: 2439: 2430: 2429: 2421: 2415: 2414: 2402: 2396: 2395: 2384: 2378: 2377: 2341: 2317:multihop routing 2306: 2304: 2303: 2298: 2275: 2273: 2272: 2267: 2265: 2264: 2218: 2216: 2215: 2210: 2181: 2179: 2178: 2173: 2171: 2170: 2133: 2131: 2130: 2125: 2123: 2122: 2107:: Leading rider 2103: 2101: 2100: 2095: 2083: 2081: 2080: 2075: 2063: 2061: 2060: 2055: 2053: 2052: 2023: 2021: 2020: 2015: 2013: 2012: 1966: 1964: 1963: 1958: 1946: 1944: 1943: 1938: 1926: 1924: 1923: 1918: 1906: 1904: 1903: 1898: 1886: 1884: 1883: 1878: 1866: 1864: 1863: 1858: 1839: 1830: 1828: 1827: 1822: 1775: 1774: 1732: 1731: 1697: 1692: 1669: 1658: 1649: 1647: 1646: 1641: 1638: 1633: 1603: 1602: 1589: 1584: 1539: 1538: 1510: 1505: 1482: 1475: 1473: 1472: 1467: 1465: 1464: 1455: 1454: 1447: 1442: 1419: 1410: 1408: 1407: 1402: 1382: 1381: 1369: 1368: 1359: 1358: 1351: 1346: 1316: 1315: 1287: 1282: 1259: 1252: 1250: 1249: 1244: 1241: 1236: 1221:coordinate, and 1220: 1218: 1217: 1212: 1210: 1209: 1190: 1188: 1187: 1182: 1180: 1179: 1160: 1158: 1157: 1152: 1149: 1144: 1122: 1120: 1119: 1114: 1102: 1100: 1099: 1094: 1092: 1091: 1075: 1073: 1072: 1067: 1048: 1039: 1037: 1036: 1031: 1022: 1017: 990: 989: 976: 971: 923: 922: 894: 889: 866: 842: 840: 839: 834: 832: 831: 815: 813: 812: 807: 805: 804: 785: 783: 782: 777: 775: 774: 751: 742: 740: 739: 734: 732: 730: 726: 725: 713: 712: 696: 650: 633: 624: 622: 621: 616: 614: 606: 566: 562: 560: 559: 554: 542: 540: 539: 534: 522: 520: 519: 514: 502: 500: 499: 494: 482: 480: 479: 474: 455: 446: 444: 443: 438: 395: 388: 386: 385: 380: 378: 377: 358: 356: 355: 350: 348: 347: 328: 326: 325: 320: 318: 317: 298: 296: 295: 290: 273: 272: 256: 254: 253: 248: 229: 220: 218: 217: 212: 156: 155: 140: 139: 122: 118: 116: 115: 110: 19: 3649: 3648: 3644: 3643: 3642: 3640: 3639: 3638: 3624: 3623: 3622: 3617: 3600: 3557: 3536: 3499: 3460: 3437: 3426: 3419: 3373: 3348: 3312: 3279: 3270: 3247: 3236: 3215: 3189: 3185:Penalty methods 3180:Barrier methods 3164: 3151: 3131: 3127:Newton's method 3109: 3061: 3024: 2992: 2973:Powell's method 2950: 2937: 2920: 2890: 2889: 2879: 2878: 2874: 2844: 2843: 2839: 2824: 2803: 2802: 2798: 2764: 2763: 2759: 2737: 2736: 2732: 2696: 2695: 2691: 2659: 2658: 2654: 2644: 2643: 2639: 2622: 2611: 2610: 2606: 2578: 2577: 2573: 2563: 2562: 2558: 2527:: 80570–80576. 2514: 2513: 2509: 2479: 2478: 2471: 2441: 2440: 2433: 2426:"GoogleScholar" 2423: 2422: 2418: 2404: 2403: 2399: 2392:Knowledge (XXG) 2388:"Metaheuristic" 2386: 2385: 2381: 2343: 2342: 2329: 2324: 2312: 2307: 2277: 2276: 2256: 2251: 2250: 2186: 2185: 2156: 2145: 2144: 2114: 2109: 2108: 2086: 2085: 2066: 2065: 2044: 2039: 2038: 1998: 1993: 1992: 1989: 1981: 1973: 1949: 1948: 1929: 1928: 1909: 1908: 1889: 1888: 1869: 1868: 1849: 1848: 1837: 1766: 1723: 1673: 1672: 1656: 1594: 1530: 1486: 1485: 1429: 1428: 1417: 1373: 1307: 1263: 1262: 1223: 1222: 1198: 1193: 1192: 1168: 1163: 1162: 1125: 1124: 1105: 1104: 1083: 1078: 1077: 1058: 1057: 1046: 981: 914: 870: 869: 857: 849: 823: 818: 817: 793: 788: 787: 766: 761: 760: 749: 717: 704: 700: 654: 653: 644: 631: 570: 569: 545: 544: 525: 524: 505: 504: 485: 484: 465: 464: 453: 399: 398: 366: 361: 360: 336: 331: 330: 306: 301: 300: 264: 259: 258: 239: 238: 227: 147: 131: 126: 125: 101: 100: 97: 89: 12: 11: 5: 3647: 3645: 3637: 3636: 3634:Metaheuristics 3626: 3625: 3619: 3618: 3616: 3615: 3609: 3606: 3605: 3602: 3601: 3599: 3598: 3593: 3588: 3583: 3578: 3573: 3568: 3562: 3559: 3558: 3555:Metaheuristics 3553: 3546: 3545: 3542: 3541: 3538: 3537: 3535: 3534: 3529: 3527:Ford–Fulkerson 3524: 3519: 3513: 3511: 3505: 3504: 3501: 3500: 3498: 3497: 3495:Floyd–Warshall 3492: 3487: 3486: 3485: 3474: 3472: 3462: 3461: 3459: 3458: 3453: 3448: 3442: 3440: 3429: 3421: 3420: 3418: 3417: 3416: 3415: 3401: 3396: 3391: 3385: 3383: 3375: 3374: 3369: 3362: 3361: 3358: 3357: 3354: 3353: 3350: 3349: 3347: 3346: 3341: 3336: 3331: 3325: 3323: 3314: 3313: 3311: 3310: 3305: 3300: 3298:Affine scaling 3294: 3292: 3290:Interior point 3283: 3272: 3271: 3269: 3268: 3263: 3258: 3252: 3250: 3238: 3237: 3232: 3225: 3224: 3221: 3220: 3217: 3216: 3214: 3213: 3208: 3203: 3197: 3195: 3194:Differentiable 3191: 3190: 3188: 3187: 3182: 3176: 3174: 3166: 3165: 3160: 3153: 3152: 3142: 3140: 3137: 3136: 3133: 3132: 3130: 3129: 3123: 3121: 3115: 3114: 3111: 3110: 3108: 3107: 3102: 3097: 3092: 3087: 3082: 3077: 3071: 3069: 3063: 3062: 3060: 3059: 3054: 3049: 3040: 3034: 3032: 3026: 3025: 3023: 3022: 3017: 3011: 3009: 3000: 2994: 2993: 2991: 2990: 2985: 2980: 2975: 2970: 2964: 2962: 2952: 2951: 2946: 2939: 2938: 2921: 2919: 2918: 2911: 2904: 2896: 2888: 2887: 2872: 2853:(3): 235–258. 2837: 2822: 2796: 2757: 2730: 2689: 2652: 2637: 2604: 2571: 2556: 2507: 2469: 2431: 2416: 2397: 2379: 2326: 2325: 2323: 2320: 2311: 2308: 2296: 2293: 2290: 2287: 2284: 2263: 2259: 2208: 2205: 2202: 2199: 2196: 2193: 2169: 2166: 2163: 2159: 2155: 2152: 2121: 2117: 2093: 2073: 2051: 2047: 2026: 2011: 2008: 2005: 2001: 1988: 1985: 1980: 1977: 1972: 1969: 1956: 1936: 1916: 1896: 1876: 1856: 1843: 1842: 1833: 1831: 1820: 1817: 1814: 1811: 1808: 1805: 1802: 1799: 1796: 1793: 1790: 1787: 1784: 1781: 1778: 1773: 1769: 1765: 1762: 1759: 1756: 1753: 1750: 1747: 1744: 1741: 1738: 1735: 1730: 1726: 1722: 1719: 1716: 1713: 1710: 1707: 1704: 1701: 1696: 1691: 1688: 1685: 1681: 1662: 1661: 1652: 1650: 1637: 1632: 1628: 1624: 1621: 1618: 1615: 1612: 1609: 1606: 1601: 1597: 1593: 1588: 1583: 1580: 1577: 1573: 1569: 1566: 1563: 1560: 1557: 1554: 1551: 1548: 1545: 1542: 1537: 1533: 1529: 1526: 1523: 1520: 1517: 1514: 1509: 1504: 1501: 1498: 1494: 1463: 1458: 1453: 1446: 1441: 1437: 1423: 1422: 1413: 1411: 1400: 1397: 1394: 1391: 1388: 1385: 1380: 1376: 1372: 1367: 1362: 1357: 1350: 1345: 1341: 1337: 1334: 1331: 1328: 1325: 1322: 1319: 1314: 1310: 1306: 1303: 1300: 1297: 1294: 1291: 1286: 1281: 1278: 1275: 1271: 1240: 1235: 1231: 1208: 1205: 1201: 1178: 1175: 1171: 1148: 1143: 1140: 1137: 1133: 1112: 1090: 1086: 1065: 1052: 1051: 1042: 1040: 1029: 1026: 1021: 1016: 1012: 1008: 1005: 1002: 999: 996: 993: 988: 984: 980: 975: 970: 967: 964: 960: 956: 953: 950: 947: 944: 941: 938: 935: 932: 929: 926: 921: 917: 913: 910: 907: 904: 901: 898: 893: 888: 885: 882: 878: 856: 853: 848: 845: 830: 826: 803: 800: 796: 773: 769: 755: 754: 745: 743: 729: 724: 720: 716: 711: 707: 703: 699: 694: 691: 688: 685: 682: 679: 676: 673: 670: 667: 664: 661: 643: 640: 637: 636: 627: 625: 612: 609: 604: 601: 598: 595: 592: 589: 586: 583: 580: 577: 552: 532: 512: 492: 472: 459: 458: 449: 447: 436: 433: 430: 427: 424: 421: 418: 415: 412: 409: 406: 389:time instant. 376: 373: 369: 346: 343: 339: 316: 313: 309: 288: 285: 282: 279: 276: 271: 267: 246: 233: 232: 223: 221: 210: 207: 204: 201: 198: 195: 192: 189: 186: 183: 180: 177: 174: 171: 168: 165: 162: 159: 154: 150: 146: 143: 138: 134: 108: 96: 93: 88: 85: 67: 66: 63: 62:Citation count 59: 58: 55: 51: 50: 47: 43: 42: 39: 35: 34: 33:Metaheuristics 31: 27: 26: 23: 13: 10: 9: 6: 4: 3: 2: 3646: 3635: 3632: 3631: 3629: 3614: 3611: 3610: 3607: 3597: 3594: 3592: 3589: 3587: 3584: 3582: 3579: 3577: 3574: 3572: 3571:Hill climbing 3569: 3567: 3564: 3563: 3560: 3556: 3551: 3547: 3533: 3530: 3528: 3525: 3523: 3520: 3518: 3515: 3514: 3512: 3510: 3509:Network flows 3506: 3496: 3493: 3491: 3488: 3484: 3481: 3480: 3479: 3476: 3475: 3473: 3471: 3470:Shortest path 3467: 3457: 3454: 3452: 3449: 3447: 3444: 3443: 3441: 3439: 3438:spanning tree 3433: 3430: 3428: 3422: 3414: 3410: 3407: 3406: 3405: 3402: 3400: 3397: 3395: 3392: 3390: 3387: 3386: 3384: 3380: 3376: 3372: 3371:Combinatorial 3367: 3363: 3345: 3342: 3340: 3337: 3335: 3332: 3330: 3327: 3326: 3324: 3322: 3319: 3315: 3309: 3306: 3304: 3301: 3299: 3296: 3295: 3293: 3291: 3287: 3284: 3282: 3277: 3273: 3267: 3264: 3262: 3259: 3257: 3254: 3253: 3251: 3249: 3243: 3239: 3235: 3230: 3226: 3212: 3209: 3207: 3204: 3202: 3199: 3198: 3196: 3192: 3186: 3183: 3181: 3178: 3177: 3175: 3171: 3167: 3163: 3158: 3154: 3146: 3128: 3125: 3124: 3122: 3120: 3116: 3106: 3103: 3101: 3098: 3096: 3093: 3091: 3088: 3086: 3083: 3081: 3078: 3076: 3073: 3072: 3070: 3068: 3067:Other methods 3064: 3058: 3055: 3053: 3050: 3048: 3044: 3041: 3039: 3036: 3035: 3033: 3031: 3027: 3021: 3018: 3016: 3013: 3012: 3010: 3008: 3004: 3001: 2999: 2995: 2989: 2986: 2984: 2981: 2979: 2976: 2974: 2971: 2969: 2966: 2965: 2963: 2961: 2957: 2953: 2949: 2944: 2940: 2936: 2932: 2928: 2924: 2917: 2912: 2910: 2905: 2903: 2898: 2897: 2894: 2883: 2876: 2873: 2868: 2864: 2860: 2856: 2852: 2848: 2841: 2838: 2833: 2829: 2825: 2819: 2815: 2811: 2807: 2800: 2797: 2792: 2788: 2784: 2780: 2776: 2772: 2768: 2761: 2758: 2753: 2749: 2745: 2741: 2734: 2731: 2726: 2722: 2717: 2712: 2708: 2704: 2700: 2693: 2690: 2685: 2681: 2677: 2673: 2669: 2665: 2664: 2656: 2653: 2648: 2641: 2638: 2633: 2627: 2619: 2615: 2608: 2605: 2599: 2594: 2590: 2586: 2582: 2575: 2572: 2567: 2560: 2557: 2552: 2548: 2543: 2538: 2534: 2530: 2526: 2522: 2518: 2511: 2508: 2503: 2499: 2495: 2491: 2487: 2483: 2476: 2474: 2470: 2465: 2461: 2457: 2453: 2449: 2445: 2438: 2436: 2432: 2427: 2420: 2417: 2412: 2408: 2401: 2398: 2393: 2389: 2383: 2380: 2375: 2371: 2367: 2363: 2359: 2355: 2351: 2347: 2340: 2338: 2336: 2334: 2332: 2328: 2321: 2319: 2318: 2309: 2294: 2291: 2288: 2285: 2282: 2261: 2257: 2248: 2247: 2242: 2241: 2236: 2235: 2230: 2229: 2224: 2223: 2206: 2203: 2200: 2197: 2194: 2191: 2184: 2167: 2164: 2161: 2157: 2153: 2150: 2143: 2139: 2138: 2119: 2115: 2106: 2091: 2071: 2049: 2045: 2036: 2033: 2029: 2025: 2009: 2006: 2003: 1999: 1986: 1984: 1978: 1976: 1970: 1968: 1954: 1934: 1914: 1894: 1874: 1854: 1841: 1834: 1832: 1809: 1803: 1800: 1797: 1791: 1785: 1782: 1779: 1771: 1767: 1763: 1757: 1751: 1748: 1742: 1739: 1736: 1728: 1724: 1717: 1714: 1708: 1705: 1702: 1694: 1689: 1686: 1683: 1679: 1671: 1670: 1667: 1660: 1653: 1651: 1635: 1630: 1622: 1613: 1610: 1607: 1599: 1595: 1591: 1586: 1581: 1578: 1575: 1571: 1567: 1564: 1561: 1555: 1549: 1546: 1543: 1535: 1531: 1527: 1521: 1518: 1515: 1507: 1502: 1499: 1496: 1492: 1484: 1483: 1480: 1477: 1456: 1444: 1439: 1435: 1421: 1414: 1412: 1392: 1389: 1386: 1378: 1374: 1370: 1360: 1348: 1343: 1339: 1332: 1326: 1323: 1320: 1312: 1308: 1304: 1298: 1295: 1292: 1284: 1279: 1276: 1273: 1269: 1261: 1260: 1257: 1254: 1238: 1233: 1206: 1203: 1199: 1176: 1173: 1169: 1146: 1141: 1138: 1135: 1131: 1110: 1088: 1084: 1063: 1050: 1043: 1041: 1019: 1014: 1006: 1000: 997: 994: 986: 982: 978: 973: 968: 965: 962: 958: 951: 948: 945: 939: 933: 930: 927: 919: 915: 911: 905: 902: 899: 891: 886: 883: 880: 876: 868: 867: 864: 861: 854: 852: 846: 844: 828: 824: 801: 798: 794: 771: 767: 753: 746: 744: 722: 718: 714: 709: 705: 697: 692: 689: 686: 683: 680: 677: 674: 671: 668: 665: 662: 659: 652: 651: 648: 641: 635: 628: 626: 610: 607: 602: 599: 596: 593: 590: 587: 584: 581: 578: 575: 568: 567: 564: 550: 530: 510: 490: 470: 457: 450: 448: 434: 431: 428: 425: 422: 419: 416: 413: 410: 407: 404: 397: 396: 393: 390: 374: 371: 367: 344: 341: 337: 314: 311: 307: 283: 280: 277: 269: 265: 244: 231: 224: 222: 208: 205: 202: 199: 196: 193: 190: 187: 184: 181: 178: 175: 166: 163: 160: 152: 148: 141: 136: 132: 124: 123: 120: 106: 94: 92: 86: 84: 80: 76: 74: 64: 60: 56: 52: 48: 44: 40: 36: 32: 28: 24: 20: 3576:Local search 3522:Edmonds–Karp 3478:Bellman–Ford 3248:minimization 3080:Gauss–Newton 3030:Quasi–Newton 3015:Trust region 2923:Optimization 2881: 2875: 2850: 2846: 2840: 2805: 2799: 2774: 2770: 2760: 2743: 2739: 2733: 2706: 2702: 2692: 2667: 2661: 2655: 2646: 2640: 2626:cite journal 2617: 2607: 2588: 2584: 2574: 2565: 2559: 2524: 2520: 2510: 2485: 2481: 2447: 2443: 2419: 2410: 2400: 2391: 2382: 2349: 2345: 2313: 2310:Applications 2244: 2238: 2232: 2226: 2220: 2182: 2141: 2135: 2104: 2034: 2031: 2027: 1990: 1982: 1974: 1846: 1835: 1665: 1654: 1478: 1426: 1415: 1255: 1055: 1044: 862: 858: 850: 758: 747: 645: 629: 462: 451: 391: 236: 225: 98: 90: 81: 77: 72: 70: 22:Developed by 3596:Tabu search 3007:Convergence 2978:Line search 2777:(6): 1–17. 2521:IEEE Access 2352:(1): 2–26. 3427:algorithms 2935:heuristics 2927:Algorithms 2649:: 163–169. 2322:References 816:rider and 3382:Paradigms 3281:quadratic 2998:Gradients 2960:Functions 2867:220687409 2832:215911629 2791:220846722 2725:219455360 2684:225249612 2551:195775696 2502:226439786 2488:(10): 1. 2464:219914332 2424:Binu, D. 2411:MathWorks 2028:algorithm 1955:δ 1915:ξ 1875:χ 1855:λ 1810:ρ 1804:δ 1801:− 1792:∗ 1786:ρ 1780:ξ 1758:ρ 1752:δ 1749:∗ 1743:ρ 1737:χ 1718:λ 1709:ρ 1627:∂ 1614:ρ 1592:∗ 1582:ρ 1572:φ 1550:ρ 1522:ρ 1445:∗ 1371:∗ 1349:∗ 1230:∂ 1191:rider in 1132:φ 1011:∂ 1007:∗ 979:∗ 959:φ 728:‖ 715:− 702:‖ 329:rider in 206:≤ 200:≤ 188:≤ 182:≤ 87:Algorithm 46:Publisher 3628:Category 3613:Software 3490:Dijkstra 3321:exchange 3119:Hessians 3085:Gradient 2374:54459927 359:size at 54:Language 30:Category 3456:Kruskal 3446:BorĹŻvka 3436:Minimum 3173:General 2931:methods 2884:: 2764. 2620:: 1–26. 2568:: 1–18. 2529:Bibcode 2354:Bibcode 1847:where, 1427:where, 1056:where, 463:where, 237:where, 3318:Basis- 3276:Linear 3246:Convex 3090:Mirror 3047:L-BFGS 2933:, and 2865:  2830:  2820:  2789:  2723:  2682:  2549:  2500:  2462:  2372:  2140:) 2105:output 2035:input: 759:where, 57:Matlab 25:Binu D 3517:Dinic 3425:Graph 2863:S2CID 2828:S2CID 2787:S2CID 2721:S2CID 2680:S2CID 2547:S2CID 2498:S2CID 2460:S2CID 2450:(3). 2370:S2CID 2142:while 3483:SPFA 3451:Prim 3045:and 2818:ISBN 2632:link 2154:< 1947:and 71:The 49:IEEE 41:2019 3413:cut 3278:and 2855:doi 2810:doi 2779:doi 2748:doi 2711:doi 2672:doi 2593:doi 2537:doi 2490:doi 2452:doi 2362:doi 2183:for 3630:: 2929:, 2925:: 2861:. 2851:16 2849:. 2826:. 2816:. 2785:. 2775:29 2773:. 2769:. 2744:63 2742:. 2719:. 2707:14 2705:. 2701:. 2678:. 2670:. 2668:21 2666:. 2628:}} 2624:{{ 2616:. 2589:34 2587:. 2583:. 2545:. 2535:. 2523:. 2519:. 2496:. 2486:68 2484:. 2472:^ 2458:. 2448:30 2446:. 2434:^ 2409:. 2390:. 2368:. 2360:. 2350:68 2348:. 2330:^ 2032:is 1907:, 65:49 3411:/ 2915:e 2908:t 2901:v 2869:. 2857:: 2834:. 2812:: 2793:. 2781:: 2754:. 2750:: 2727:. 2713:: 2686:. 2674:: 2634:) 2601:. 2595:: 2553:. 2539:: 2531:: 2525:7 2504:. 2492:: 2466:. 2454:: 2428:. 2413:. 2394:. 2376:. 2364:: 2356:: 2295:1 2292:+ 2289:l 2286:= 2283:l 2262:G 2258:S 2246:4 2240:8 2234:7 2228:6 2222:5 2207:P 2204:o 2201:t 2198:1 2195:= 2192:v 2168:F 2165:F 2162:O 2158:L 2151:l 2137:4 2120:G 2116:S 2092:L 2072:l 2050:l 2046:S 2010:F 2007:F 2004:O 2000:L 1935:P 1895:P 1840:) 1838:8 1836:( 1819:] 1816:] 1813:) 1807:( 1798:1 1795:[ 1789:) 1783:, 1777:( 1772:l 1768:S 1764:+ 1761:) 1755:( 1746:) 1740:, 1734:( 1729:l 1725:S 1721:[ 1715:= 1712:) 1706:, 1703:v 1700:( 1695:b 1690:1 1687:+ 1684:l 1680:S 1659:) 1657:7 1655:( 1636:l 1631:v 1623:+ 1620:] 1617:) 1611:, 1608:G 1605:( 1600:G 1596:S 1587:l 1579:, 1576:v 1568:s 1565:o 1562:c 1559:[ 1556:+ 1553:) 1547:, 1544:G 1541:( 1536:G 1532:S 1528:= 1525:) 1519:, 1516:v 1513:( 1508:a 1503:1 1500:+ 1497:l 1493:S 1462:) 1457:v 1452:( 1440:l 1436:D 1420:) 1418:6 1416:( 1399:] 1396:) 1393:o 1390:, 1387:G 1384:( 1379:G 1375:S 1366:) 1361:v 1356:( 1344:l 1340:D 1336:[ 1333:+ 1330:) 1327:o 1324:, 1321:v 1318:( 1313:l 1309:S 1305:= 1302:) 1299:o 1296:, 1293:v 1290:( 1285:o 1280:1 1277:+ 1274:l 1270:S 1239:l 1234:v 1207:h 1204:t 1200:o 1177:h 1174:t 1170:v 1147:l 1142:o 1139:, 1136:v 1111:G 1089:G 1085:S 1064:o 1049:) 1047:5 1045:( 1028:] 1025:) 1020:l 1015:v 1004:) 1001:o 998:, 995:G 992:( 987:G 983:S 974:l 969:o 966:, 963:v 955:( 952:s 949:o 946:c 943:[ 940:+ 937:) 934:o 931:, 928:G 925:( 920:G 916:S 912:= 909:) 906:o 903:, 900:v 897:( 892:f 887:1 884:+ 881:l 877:S 829:t 825:l 802:h 799:t 795:v 772:v 768:S 752:) 750:4 748:( 723:t 719:l 710:v 706:S 698:1 693:= 690:e 687:t 684:a 681:r 678:s 675:s 672:e 669:c 666:c 663:u 660:S 634:) 632:3 630:( 611:5 608:P 603:= 600:K 597:+ 594:A 591:+ 588:O 585:+ 582:J 579:+ 576:B 551:K 531:A 511:O 491:J 471:B 456:) 454:2 452:( 435:K 432:+ 429:A 426:+ 423:O 420:+ 417:J 414:+ 411:B 408:= 405:P 375:h 372:t 368:l 345:h 342:t 338:k 315:h 312:t 308:v 287:) 284:k 281:, 278:v 275:( 270:l 266:S 245:P 230:) 228:1 226:( 209:W 203:k 197:1 194:, 191:P 185:v 179:1 176:; 173:} 170:) 167:k 164:, 161:v 158:( 153:l 149:S 145:{ 142:= 137:l 133:S 107:V

Index

4
5
6
7
8
4
multihop routing





Bibcode
2019ITIM...68....2B
doi
10.1109/TIM.2018.2836058
S2CID
54459927
"Metaheuristic"
"Rider Optimization Algorithm"
"GoogleScholar"


doi
10.1142/S0218126621500481
S2CID
219914332


doi

Text is available under the Creative Commons Attribution-ShareAlike License. Additional terms may apply.

↑