A hybrid SA-EA method for finding the maximum number of switching gates in a combinational circuit

Obregon, Ichiro R. Ruiz; Pawlovsky, Alberto Palacios

doi:10.1587/elex.5.756

Cited by 3 publications

(2 citation statements)

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“…e intersection position between line A ′ B(y � a ′ x + b ′ ) and line segment of storage area (y � a s x + b s ) is position C(X s1 , Y s1 ). When X 2 � X 1 ′ , position C is shown in formula (7). When X 2 ≠ X 1 ′ , position C is shown in formula (8):…”

Section: Determination Of Storage Positions As Shown Inmentioning

confidence: 99%

“…e picking path of A. bisporus can be optimized by the searching algorithm. Search algorithms are applied to various occasions [4][5][6][7], and one of them is applied to TSP (traveling salesman problem) model [8]. e TSP model is a typical combinatorial optimization problem, which can be expressed as a person needs to go through several cities, he needs to start from a city (the city can be fixed or not fixed), go through all cities and only once, and finally return to the starting position.…”

Section: Introductionmentioning

confidence: 99%

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Picking Path Optimization of Agaricus bisporus Picking Robot

Zhaoren

2019

Mathematical Problems in Engineering

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The design and application of the mushroom picking robot will greatly reduce the labor cost, and it has become one of the research hotspots in the world. Therefore, we independently developed an A. bisporus (a kind of mushroom) picking robot and introduced its functional principle in this paper. At the same time, in order to improve the picking efficiency of the picking robot, a picking path optimization algorithm based on TSP model is proposed. Firstly, based on the TSP model, a picking route model for A. bisporus was established to determine the storage location of each A. bisporus. Then, an improved simulated annealing (I-SA) search algorithm is proposed to find the optimal path sequence. By improving the path initialization module, path generation module, and temperature drop module, the I-SA search algorithm can optimize the picking path in a short time. Finally, in order to improve the stability and reduce the running time of the I-SA search algorithm, a parallel optimization method for global search (“rough exploration”) and local search (“precision exploration”) is proposed. Through simulation experiments, the I-SA search algorithm can search stable and excellent path solution in a relatively short time. Through field experiments on mushroom base, the efficiency of picking A. bisporus can be improved by 14% to 18%, which verifies the effectiveness of the I-SA search algorithm.

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Section: Determination Of Storage Positions As Shown Inmentioning

confidence: 99%