Jia Ma's research while affiliated with Chinese Academy of Sciences and other places
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Publications (10)
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...
The flexible job-shop scheduling problem (FJSP) is one of the most general and difficult of all traditional scheduling problem. The paper presents a novelty immune genetic algorithm (IGA) to solve the problem. This algorithm preserves the random global search ability of simple genetic algorithm (SGA), and introduces the immune mechanism by which th...
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...
The study introduces an immune clonal algorithm (ICA), which depends on Artificial Immune System principles, for traditional facility layout problems. The new algorithm through the introduction of clonal proliferation, super mutation operators and clonal selection operators, improves the global convergence speed, and can effectively avoid prematuri...
Analyzing the model of the single level capacitated lot-sizing problem (SLCLSP), a new approach based on IGA (immune genetic algorithm) is proposed to solve the problem. It not only retains the global research ability of SGA (simple genetic algorithm) but also adopts some strategies to keep up the diversity of biological immunity mechanism so as to...
Aiming at the precocious convergence problem of particle swarm optimization algorithm, adaptive particle swarm optimization(APSO) algorithm was presented. In this algorithm, the notion of species was introduced into population diversity measure. The species technique is based on the concept of dividing the population into several species according...
The bullwhip effect which brought by supplier implementing the linear assignment mechanism in the condition of supply deficiency was analyzed, and then two reasonable allocation measures to restrain the bullwhip effect were offered. One is based on historical data; the other is based on retailers' retractile ratio, which includes the production ass...
Focused on the VRPTW (vehicle routing problem with time windows) and based on SGA (simple genetic algorithm), this paper employs a new IGA (immune genetic algorithm) to solve the VRPTW through using immune operator. This algorithm based on the global searching method of SGA, and using the diversity preservation strategy of antibodies in biology imm...
A bstract-Analyzing the model of the flexible job-shop scheduling problem(F JSP),an immune genetic algorithm(IGA) is proposed to solve the problem. This algorithm preserves the random global search ability of simple genetic algorithm(SGA), and introduces the immune mechanism by which the necessary vaccine may be extracted with the scheduling vaccin...
Citations
... In their proposed algorithm, some simple local search methods are used to balance exploration and exploitation. Ma et al. [83] proposed a memetic algorithm (MA) to solve the FJSP. The MA is a hybrid GA combined with two efficient local searches to exploit information in the search region. ...
Reference: Review on flexible job shop scheduling
... Hazrai and Sinha have done active and reactive power optimization via particle swarm algorithm [3]. Li. et al. have used adaptive particle swarm algorithm [4]. Wei et al. and Chen et al. have used basic immunity in genetic algorithm (GA) and advance GA methods in RPO respectively [5,6]. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/306410166915073-1450065284717_Q64/Yang-Li-448.jpg)
... From the operational perspective, the transportation planning of the vehicles and the routes has been investigated for vaccine cold chains. In this regard, the time window is an important consideration to ensure responsive vaccine delivery (Ma et al., 2006). Zheng et al. (2013) investigated a capacitated vehicle routing problem (CVRP) with breakdowns for the last-mile vaccine distribution. ...
... 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. ...
