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A distributed permutation flow shop scheduling problem (DPFSP) is an NP-hard problem recently put forward in shop scheduling sphere. Exact algorithms for a DPFSP's solution can be extremely computationally costly. This paper proposes to apply an electromagnetism-like mechanism (EM) algorithm as a heuristic solution method to a DPFSP. To fit into the discrete domain of a DPFSP, modifications to the...
Flexible job shop scheduling problem (FJSP) is an important extension of the classical job shop scheduling problem, where the same operation could be processed on more than one machine. Owing to the high computational complexity, it is quite difficult to achieve an optimal solution with traditional optimization approaches. An improved genetic algorithm combined with tabu search is proposed to solve...
This paper proposes a new algorithm for topology optimization by combining the features of genetic algorithms (GAs) and optimality criteria method (OC). An efficient treatment of initial population with optimality criteria method for evolutionary algorithm is presented which is different from traditional GAs application in structural topology optimization. The optimality method initializes a group...
Process planning is an essential part for a Computer Aided Process Planning (CAPP) system in the dynamic workshop environment. It is a combinatorial optimization problem to conduct operations selection and operations sequencing simultaneously with various constraints deriving from practical workshop environment as well as the part to be processed. In this paper, a hybrid genetic simulated annealing...
In electric power market, the research of best bidding price is an important study, in which the calculation and description of node price is the key issue. Based on the highly effective ant colony algorithm, this paper proposes a methodology of best bidding for solving the optimal price model of the electric power market. We use the random global search capability of ant colony algorithm to deal...
Flexible job shop scheduling problem (FJSP) is an important extension of the classical job shop scheduling problem, where the same operation could be processed on more than one machine. An improved genetic algorithm combined with local search is proposed to solve the FJSP with makespan criterion. To control the local search and convergence to the global optimal solution, time-varying crossover probability...
The theory and applications of artificial neural networks have developed rapidly since the mathematical model of neuron was presented, but the design of network structure for a certain problem was a roadblock over a long period of time. In 1990s, the covering algorithm for forward neural network was put forward, this algorithm is a constructive machine learning method, it designs network with sphere...
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