Abstract Efficient and accurate porosity prediction is essential for the fine description of reservoirs, which an optimized BP neural network (BPNN) model proposed. Aiming at problem that BPNN sensitive to initialization converges local optimum easily, improved shuffled frog leaping algorithm (ISFLA) proposed based on roulette genetic coding. Firstly, a mechanism introduced improve selection pr...

In distribution systems, in order to diminish power losses and keep voltage profiles within acceptable limits, network reconfiguration and capacitor placement are commonly used. In this paper, the Hybrid Shuffled Frog Leaping Algorithm (HSFLA) is used to optimize balanced and unbalanced radial distribution systems by means of a network reconfiguration and capacitor placement. High accuracy and ...

The Job Shop Scheduling Problem (JSSP) is a well known practical planning problem in the manufacturing sector. We have considered the JSSP with an objective of minimizing makespan. In this paper, we develop a three-stage hybrid approach called JSFMA to solve the JSSP. In JSFMA, considering a method similar to Shuffled Frog Leaping algorithm we divide the population in several sub populations an...

Congestion pricing strategy has been recognized as an effective countermeasure in the practical field of urban traffic congestion mitigation. In this paper, a bi-level programming model considering carbon dioxide emission is proposed to mitigate traffic congestion and reduce carbon dioxide emissions. The objective function of the upper level model is to minimize the sum of travel costs and the ...

Production planning and scheduling in the steel industry are challenging problems due to large number of products being produced. This work deals with scheduling of the continuous casting of steelmaking, i.e. determination of charge sequence in each casting machine. Since a full-space model Mixed-Integer Linear Programming (MILP) approach is computationally intractable for long term continuous ...

In this paper, the Shuffled Frog Leaping Algorithm is proposed to solve the Profit Based Unit Commitment problem under deregulated environment with emission limitation. The bi-objective function optimization problem is formulated as a maximization of the Generation Companies profit and a minimization of the emission output of the thermal units, while all of the constrains should be satisfied. T...