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Faculty

Weishi Shao

Academic Area: 
Decision and optimization
Research Interests: 
  • Production scheduling
  • Meta-heuristics
  • Heuristics
  • Evolutionary computation
  • Combinatorial optimization
Bio: 

Educational Background:

 

Ph.D., Computer Science and Technology, Nanjing University of Aeronautics and Astronautics (2018)

M. Eng., Computer Software and Theory, Lanzhou University (2015)

B. Mgt., Information Management and Information System, Anhui Polytechnic University (2012)

 

Research

Research Projects

Research on large-scale complex production process scheduling methods based on collaborative learning, Funding of Jiangsu Innovation Program for Graduate Education (KYLX16_0382)

 

Journal Articles

  • Shao Weishi, Pi Dechang, and Shao Zhongshi. A Pareto-based estimation of distribution algorithm for solving multi-objective distributed no-wait flow-shop scheduling problem with sequence-dependent setup time, IEEE Transactions on Automation Science and Engineering (accepted DOI: 10.1109/TASE.2018.2886303) (SCI, IF: 3.667, CCF-B)
  • Shao Weishi, Pi Dechang, and Shao Zhongshi. Local search methods for distributed assembly no-idle flow shop scheduling problem, IEEE Systems Journal, Vol. 13(2), pp. 1945-1956, 2019. (SCI, IF: 4.337)
  • Shao Weishi, Pi Dechang, and Shao Zhongshi. A hybrid discrete teaching-learning based meta-heuristic for solving no-idle flowshop scheduling problem with total tardiness criterion, Computers & Operations Research, Vol. 94, pp. 89-105, 2018. (SCI, IF:2.962)
  • Shao Weishi, Pi Dechang, and Shao Zhongshi. Optimization of makespan for the distributed no-wait flow shop scheduling problem with iterated greedy algorithms, Knowledge-Based Systems, Vol. 137, pp. 163-181, 2017. (SCI, IF: 4.396, CCF-C)
  • Shao Weishi, Pi Dechang, and Shao Zhongshi. An extended teaching-learning based optimization algorithm for solving no-wait flow shop scheduling problem, Applied Soft Computing, Vol. 61, pp. 193-210, 2017. (SCI, IF: 4.004)
  • Shao Weishi, Pi Dechang, and Shao Zhongshi. Memetic algorithm with node and edge histogram for no-idle flow shop scheduling problem to minimize the makespan criterion, Applied Soft Computing, Vol. 54, pp. 164-182, 2017. (SCI, IF: 4.004)
  • Shao Weishi, Pi Dechang, and Shao Zhongshi. A hybrid discrete optimization algorithm based on teaching–probabilistic learning mechanism for no-wait flow shop scheduling, Knowledge-Based Systems, Vol. 107, pp. 219-234, 2016. (SCI, IF: 4.396, CCF-C)
  • Shao Weishi, Pi Dechang. A self-guided differential evolution with neighborhood search for permutation flow shop scheduling, Expert Systems with Applications, Vol. 51, pp. 161-176, 2016. (SCI, IF: 3. 711, CCF-C)
  • Shao Zhongshi, Pi Dechang, Shao Weishi, and Yuan Peisen. An efficient discrete invasive weed optimization for blocking flow-shop scheduling problem. Engineering Applications of Artificial Intelligence, 2019, 78, 124-141. (SCI, IF: 2.819, CCF-C)
  • Shao Zhongshi, Pi Dechang, Shao Weishi. A novel multi-objective discrete water wave optimization for solving multi-objective blocking flow-shop scheduling problem. Knowledge-Based Systems, 2019, 65, 110-131. (SCI, IF: 4.396, CCF-C)
  • Shao Zhongshi, Pi Dechang, Shao Weishi. A multi-objective discrete invasive weed optimization for multi-objective blocking flow-shop scheduling problem. Expert Systems with Applications. 2018, 113, 77-99. (SCI, IF: 3.768, CCF-C)
  • Shao Zhongshi, Pi Dechang, Shao Weishi. A novel discrete water wave optimization algorithm for blocking flow-shop scheduling problem with sequence-dependent setup times. Swarm and Evolutionary Computation, 2018, 40, 53-75. (SCI, IF: 3.818)
  • Shao Zhongshi, Pi Dechang., Shao Weishi. Self-adaptive discrete invasive weed optimization for the blocking flow-shop scheduling problem to minimize total tardiness. Computers & Industrial Engineering, 2017, 111, 331-351. (SCI, IF: 3.195)
  • Shao Zhongshi, Pi Dechang., Shao Weishi. Estimation of distribution algorithm with path relinking for the blocking flow-shop scheduling problem. Engineering Optimization, 2018, 50(5), 894-916. (SCI, IF: 1.622)
  • Shao Zhongshi, Pi Dechang., Shao Weishi. An extended continuous estimation of distribution algorithm for solving the permutation flow-shop scheduling problem. Engineering Optimization, 2017, 49(11), 1868-1889. (SCI, IF: 1.622)

 

Conference Papers:

  • Shao Weishi, Pi Dechang, and Shao Zhongshi. A hybrid iterated greedy algorithm for the distributed no-wait flow shop scheduling problem, 2017 IEEE Congress on Evolutionary Computation (CEC), Donostia-San Sebastian, Spain, 5-8 June 2017, IEEE. 

 

 

Contact:

shaoweishi@hotmail.com/shaoweishi@nju.edu.cn