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A total tardiness transport plan scheduling algorithm based on improved particle swarm optimization

A technique for improving particle swarm and scheduling algorithms, applied in computing, computing models, instruments, etc.

Active Publication Date: 2016-12-14
SUN YAT SEN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, there are many kinds of existing automated factory design algorithms, and there are still areas to be improved in terms of internal data processing efficiency and the optimization degree of solutions determined in response to multiple variables.

Method used

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  • A total tardiness transport plan scheduling algorithm based on improved particle swarm optimization
  • A total tardiness transport plan scheduling algorithm based on improved particle swarm optimization
  • A total tardiness transport plan scheduling algorithm based on improved particle swarm optimization

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Embodiment Construction

[0035] Below in conjunction with the accompanying drawings, the specific embodiments of the present invention will be further described in detail, so as to make the technical solution of the present invention easier to understand and grasp.

[0036] In order to further understand this scheme, first, a brief description of the ant algorithm is given.

[0037] 1. Research on Ant Algorithm

[0038] figure 1 , assuming that point A is the ant's cave, point D is the food source, and EF is a big obstacle. Ants have two paths ABECD and ABFCD connecting the burrow and food due to obstacles. The distance between BE and EC is 1, while the distance between BF and FC is 0.5. It can be seen that the path ABFCD is the shortest path. Assume that in each time unit, there are 30 ants from point A to point D, and 30 ants from D to point A, and the amount of information left by the ants is 1. For the sake of simplicity, let the pheromone only stay 1 on the path. At the initial time, there i...

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Abstract

The invention provides a total tardiness transport plan scheduling algorithm based on improved particle swarm optimization. The algorithm comprises the steps of firstly, establishing a total tardiness value mathematic model based on input variables and defining the number n of to-be-processed works and the number m of machines, and the time pj required for processing of each to-be-processed work and the delivery term dj; secondly, solving a construction drawing according to the total tardiness value mathematic model; thirdly, based on the construction drawing and according to state transition rules and pheromone update rules, completing search and acquiring a solution making the total tardiness T minimum. Based on the ant colony algorithm and according to the characteristics of the total tardiness transport plan scheduling problem (P / / T) of parallel machines, the improved Heuristic Ant Colony Optimization (hACO) is proposed and performance optimization research is performed on the algorithm to improve the determination accuracy of optimal solutions of events and guarantee the internal data processing and screening efficiency.

Description

technical field [0001] The invention relates to a scheduling algorithm for total delayed transport planning based on improved particle swarm optimization. Background technique [0002] The total delay transportation planning problem (TTP) is a classic problem in the scheduling problem, which contains many different sub-problems, and can be generally divided into single machine (single machine) total delay and multimachines (multimachines) total delay according to the configuration of the machine. Delayed transportation planning scheduling problem. Among them, the different situations of the single machine total delay transportation planning scheduling problem are divided into the same arrival time (equal release time), different arrival time (unequal release time) and the single machine total delay transportation planning scheduling problem with weights (the single machine total weighted tardiness problem, SMTWTP). The multi-machine total delay transportation planning sche...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06N3/00
CPCG06N3/006G06Q10/04
Inventor 衣杨李芳吴斯扬涂冠平陈新耿赵勇宪
Owner SUN YAT SEN UNIV
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