[1]Bai T, Wei J, Yang WW, et al., 2018. Multi-objective parameter estimation of improved Muskingum model by wolf pack algorithm and its application in upper Hanjiang River, China. Water, 10(10):1415.
[2]Brotcorne L, Hanafi S, Mansi R, 2013. One-level reformulation of the bilevel knapsack problem using dynamic programming. Dis Optim, 10(1):1-10.
[3]Caprara A, Carvalho M, Lodi A, et al., 2014. A study on the computational complexity of the bilevel knapsack problem. SIAM J Optim, 24(2):823-838.
[4]Carvalho M, Lodi A, Marcotte P, 2018. A polynomial algorithm for a continuous bilevel knapsack problem. Oper Res Lett, 46(2):185-188.
[5]Chih M, Lin CJ, Chern MS, et al., 2014. Particle swarm optimization with time-varying acceleration coefficients for the multidimensional knapsack problem. Appl Math Model, 38(4):1338-1350.
[6]Cohn AM, Barnhart C, 1998. The stochastic knapsack problem with random weights: a heuristic approach to robust transportation planning. Proc Triennial Symp on Transportation Analysis, p.1-13.
[7]Dempe S, Richter K, 2000. Bilevel programming with knapsack constraints. Centr Eur J Oper Res, 8(2):93-107.
[8]Gao F, Cui G, Wu ZB, et al., 2009. Virus-evolutionary particle swarm optimization algorithm for knapsack problem. J Harbin Inst Technol, 41(6):103-107 (in Chinese).
[9]Gao YJ, Zhang FM, Zhao Y, et al., 2019. A novel quantum- inspired binary wolf pack algorithm for difficult knapsack problem. Int J Wirel Mob Comput, 16(3):222-232.
[10]Gherboudj A, Layeb A, Chikhi S, 2012. Solving 0-1 knapsack problems by a discrete binary version of cuckoo search algorithm. Int J Bio-Inspir Comput, 4(4):229-236.
[11]Han ZH, Tian XT, Ma XF, et al., 2018. Scheduling for re-entrant hybrid flowshop based on wolf pack algorithm. IOP Conf Ser Mater Sci Eng, 382(3):032007.
[12]Li H, Zhang L, Jiao YC, 2014. Solution for integer linear bilevel programming problems using orthogonal genetic algorithm. J Syst Eng Electron, 25(3):443-451.
[13]Li H, Xiao RB, Wu HS, 2016. Modelling for combat task allocation problem of aerial swarm and its solution using wolf pack algorithm. Int J Innov Comput Appl, 7(1): 50-59.
[14]Liu B, 2009a. Some research problems in uncertainty theory. J Uncert Syst, 3(1):3-10.
[15]Liu B, 2009b. Theory and Practice of Uncertain Programming. Springer Verlag, Berlin, Germany.
[16]Liu B, 2010. Uncertainty Theory: a Branch of Mathematics for Modeling Human Uncertainty. Springer Verlag, Berlin, Germany.
[17]Liu B, 2016. Uncertainty Theory (5th Ed.). Springer Verlag, Berlin, Germany.
[18]Liu JQ, He YC, Gu QQ, 2007. Solving knapsack problem based on discrete particle swarm optimization. Comput Eng Des, 28(13):3189-3191, 3204 (in Chinese).
[19]Özaltın OY, Prokopyev OA, Schaefer AJ, 2010. The bilevel knapsack problem with stochastic right-hand sides. Oper Res Lett, 38(4):328-333.
[20]Qian J, Zheng JG, 2012. Greedy quantum-inspired evolutionary algorithm for quadratic knapsack problem. Comput Integr Manuf Syst, 18(9):2003-2011 (in Chinese).
[21]Qiu X, Kern W, 2015. Improved approximation algorithms for a bilevel knapsack problem. Theor Comput Sci, 595(30): 120-129.
[22]Wang R, Guo N, Xiang FH, et al., 2012. An improved quantum genetic algorithm with mutation and its application to 0-1 knapsack problem. Proc Int Conf on Measurement, Information and Control, p.484-488.
[23]Wang ZT, Guo JS, Zheng MF, et al., 2015. A new approach for uncertain multiobjective programming problem based on E principle. J Ind Manag Optim, 11(1):13-26.
[24]Wu HS, Zhang FM, Wu LS, 2013. New swarm intelligence algorithm―wolf pack algorithm. Syst Eng Electron, 35(11):2430-2438 (in Chinese).
[25]Xue JJ, Wang Y, Li H, et al., 2016. A smart wolf pack algorithm and its convergence analysis. Contr Dec, 31(12):2131-2139 (in Chinese).
<2615>
<1676>
ORCID: 
Open peer comments: Debate/Discuss/Question/Opinion
<1>