Gang Shi's research while affiliated with Northeastern University (Shenyang, China) and other places
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Publications (3)
To avoid premature and guarantee the diversity of the population, an adaptive immune genetic algorithm(AIGA) is proposed to solve these problems. In this method, the AIGA flow structure is presented via combining the immune regulating mechanism and the genetic algorithm. Experimental results showed that the proposed AIGA can rise above efficiently...
An kind of immune genetic algorithm(IGA) is proposed for solving the flexible job-shop scheduling problem(FJSP). Based on the globalsearching method of classic genetic algorithm (SG), and using the diversity preservation strategy of antibodies in biology immunity mechanism, the method greatly improves the colony diversity of GA and compared to gene...
VRP is the problem of NP of a kind of typical case. This paper is put forward an improved immune clonal selection algorithm (ICSA) through introducing cloning operator to solve the VRP problem. The algorithm through the introduction of clonal proliferation, super mutation operators and clonal selection operators, improves the global convergence spe...
Citations
... The results showed that their algorithm was a feasible and effective method for the VRP. For example, the authors of [13] applied clonal selection to tackle the VRP by using clonal selection operators, super mutation operators, and clonal proliferation to improve global convergence speed. The results indicate that their algorithm has a remarkable reliability of global convergence and avoids prematurity when solving the VRP effectively. ...
... To be exact, IGA utilizes the local information to intervene in the global search process and restrain or avoid repetitive and useless work to overcome the blindness in crossover and mutation operations. This advantage inspires several studies use IGA for solving dynamic scheduling problems, because it significantly increases the algorithmic performance to find the global optimal solution in a complicated solution space [52], [54]. Therefore, given the dynamic characteristic of the fleet scheduling problem, the IGA is well-suited for the inner-level procedure. ...
