A Multiobjective Genetic Algorithm Based on a Discrete Selection Procedure

© 2015 Qiang Long et al. Multiobjective genetic algorithm (MOGA) is a direct search method for multiobjective optimization problems. It is based on the process of the genetic algorithm; the population-based property of the genetic algorithm is well applied in MOGAs. Comparing with the traditional multiobjective algorithm whose aim is to find a single Pareto solution, the MOGA intends to identify numbers of Pareto solutions. During the process of solving multiobjective optimization problems using genetic algorithm, one needs to consider the elitism and diversity of solutions. But, normally, there are some trade-offs between the elitism and diversity. For some multiobjective problems, elitism and diversity are conflicting with each other. Therefore, solutions obtained by applying MOGAs have to be balanced with respect to elitism and diversity. In this paper, we propose metrics to numerically measure the elitism and diversity of solutions, and the optimum order method is applied to identify these solutions with better elitism and diversity metrics. We test the proposed method by some well-known benchmarks and compare its numerical performance with other MOGAs; the result shows that the proposed method is efficient and robust

Sparsity-enhanced optimization for ejector performance prediction

Within a model of the ejector performance prediction, the influence of ejector component efficiencies is critical in the prediction accuracy of the model. In this paper, a unified method is developed based on sparsity-enhanced optimization to determine correlation equations of ejector component efficiencies in order to improve the prediction accuracy of the ejector performance. An ensemble algorithm that combines simulated annealing and gradient descent algorithm is proposed to obtain its global solution for the proposed optimization problem. The ejector performance prediction of a 1-D model in the literature is used as an example to illustrate and validate the proposed method. Tests results reveal that the maximum and average absolute errors for the ejector performance prediction are reduced much more when compared with existing results under the same experimental condition. Furthermore, the results indicate that the ratio of geometric parameters to operating parameters is a key factor affecting the ejector performance

Binary artificial algae algorithm for multidimensional knapsack problems

The multidimensional knapsack problem (MKP) is a well-known NP-hard optimization problem. Various meta-heuristic methods are dedicated to solve this problem in literature. Recently a new meta-heuristic algorithm, called artificial algae algorithm (AAA), was presented, which has been successfully applied to solve various continuous optimization problems. However, due to its continuous nature, AAA cannot settle the discrete problem straightforwardly such as MKP. In view of this, this paper proposes a binary artificial algae algorithm (BAAA) to efficiently solve MKP. This algorithm is composed of discrete process, repair operators and elite local search. In discrete process, two logistic functions with different coefficients of curve are studied to achieve good discrete process results. Repair operators are performed to make the solution feasible and increase the efficiency. Finally, elite local search is introduced to improve the quality of solutions. To demonstrate the efficiency of our proposed algorithm, simulations and evaluations are carried out with total of 94 benchmark problems and compared with other bio-inspired state-of-the-art algorithms in the recent years including MBPSO, BPSOTVAC, CBPSOTVAC, GADS, bAFSA, and IbAFSA. The results show the superiority of BAAA to many compared existing algorithms

TREATMENT OF THORACOLUMBAR FRACTURES BY CLOSED REDUCTION VIA A PERCUTANEOUS SOLID PEDICLE SCREW

ABSTRACT Objectives: Investigate the effect of closed reduction and per- cutaneous pedicle screw fixation in treating thoracolumbar fractures. Methods: This retrospective study analyzed 12 cases of single-segment thoracolumbar spine fractures without spinal cord and nerve injury at our department from March 2016 to September 2017. Patients were treated with closed reduction, percutaneous reduction, and internal fixation with solid pedicle screws. The operation time, intraoperative blood loss, anterior vertebral body height ratio (AVHR), Cobb angle (CA) of sagittal kyphosis, and VAS of back pain were determined and statistically compared. Results: The average operation time was 147.2 ± 45.6 min, and the average intraoperative bleeding was 67.8 ± 34.2 mL. All fractured vertebrae were completely reduced, their height was restored, and kyphosis was corrected. The average follow-up period was 10.6 ± 2.7 months, with significant improvements seen in the AVHR, CA of sagittal kyphosis, and VAS score (P < 0.01). One case had a broken rod after three months, and another had a postoperative infection. All the patients achieved bony healing. Conclusion: The treatment of thoracolumbar fractures by closed reduction and internal fixation with a percutaneous solid pedicle screw is simple, effective, and economical. Level of Evidence VI; Therapeutic Study, Case Series