摘要
Considering the low efficiency and lack of intelligent dispatching decision of the agricultural machinery scheduling problem, an improved Immune-Tabu Search Algorithm(ITSA) based on the immune optimization algorithm is proposed. A new operator, named TSA, is designed through improvement on the generation of neighborhood solution based on the tabu search algorithm. At the beginning of the iterations, the algorithm makes use of the search results of TSA as the mutated antibodies, so as to improve the climbing performance of the algorithm and accelerate the convergence speed in the meantime. Then, random mutation and tabu search for parallel strategies are implemented to ensure the optimization of the result as well as shorten the optimization time. Compared with the immune optimization algorithm and tabu search algorithm, the simulation results show that ITSA can not only obtain a better search success rate, but also stabilize the results of the algorithm.
Considering the low efficiency and lack of intelligent dispatching decision of the agricultural machinery scheduling problem, an improved Immune-Tabu Search Algorithm(ITSA) based on the immune optimization algorithm is proposed. A new operator, named TSA, is designed through improvement on the generation of neighborhood solution based on the tabu search algorithm. At the beginning of the iterations, the algorithm makes use of the search results of TSA as the mutated antibodies, so as to improve the climbing performance of the algorithm and accelerate the convergence speed in the meantime. Then, random mutation and tabu search for parallel strategies are implemented to ensure the optimization of the result as well as shorten the optimization time. Compared with the immune optimization algorithm and tabu search algorithm, the simulation results show that ITSA can not only obtain a better search success rate, but also stabilize the results of the algorithm.
引文
[1]Guan S,Morikazu N,Takeshi S,et al.Hybrid Petri nets modeling for farm work flow[J].Computers&Electronics in Agriculture,2008,62(2):149-158.
[2]Guan S,Nakamura M,Shikanai T,et al.Resource assignment and scheduling based on a two-phase metaheuristic for cropping system[J].Computers&Electronics in Agriculture,2009,66(2):181-190.
[3]Edwards G,Sorensen C G,Bochtis D D,et al.Optimised schedules for sequential agricultural operations using a Tabu Search method[J].Computers&El4ectronics in Agriculture,2015,117:102-113.
[4]Conesa-Mu?oz J,Pajares G,Ribeiro A.Mix-opt:A new route operator for optimal coverage path planning for a fleet in an agricultural environment[J].Expert Systems with Applications,2016,54:364-378.
[5]Bochtis D D,Sorensen C G C,Busato P.Advances in agricultural machinery management:A review[J].Biosystems Engineering,2014,126(39):69-81.
[6]Gutman P O,Ioslovich I.Inter-field routes scheduling and rescheduling for an autonomous tractor fleet at the farm[C]//International Conference on Methods and MODELS in Automation and Robotics.2013:812-817.
[7]Kim G,Ong Y S,Cheong T,et al.Solving the Dynamic Vehicle Routing Problem Under Traffic Congestion[J].IEEE Transactions on Intelligent Transportation Systems,2016,17(8):1-14.
[8]Yao G,Ding Y,Ren L,et al.An immune system-inspired rescheduling algorithm for workflow in Cloud systems[J].Knowledge-Based Systems,2016,99:39-50.
[9]Chen H C,Chen B B,Guo D H,et al.An Intelligent Artificial System:Artificial Immune based Hybrid Genetic Algorithm for the Vehicle Routing Problem[J].Applied Mathematics&Information Sciences,2014,8(3):1191-1200.
[10]Liu G,He Y,Qiu Y,et al.Research on influence of solving quality based on different initializing solution algorithm in tabu search[C]//Communications,Circuits and Systems and West Sino Expositions,IEEE 2002 International Conference on.IEEE Xplore,2002:1141-1145 vol.2.
[11]Lai D S W,Demirag O C,Leung J M Y.A tabu search heuristic for the heterogeneous vehicle routing problem on a multigraph[J].Transportation Research Part E Logistics&Transportation Review,2016,86:32-52.
[12]Dominguez O,Guimarans D,Juan A A,et al.A Biased-Randomised Large Neighbourhood Search for the two-dimensional Vehicle Routing Problem with Backhauls[J].European Journal of Operational Research,2016,255(2):442-462.
[13]Bochtis D D,S?rensen C G,Vougioukas S G.Path planning for in-field navigation-aiding of service units[J].Computers&Electronics in Agriculture,2010,74(1):80-90.
[14]Yu L,Cai Z,Gao P,et al.A spatial orthogonal allocation and heterogeneous cultural hybrid algorithm for multirobot exploration mission planning[J].Control Theory and Technology,2011,9(2):171-176.
