Research on Grid Planning of Dual Power Distribution Network Based on Parallel Ant Colony Optimization Algorithm

A distribution network plays an extremely important role in the safe and efficient operation of a power grid.As the core part of a power grid’s operation,a distribution network will have a significant impact on the safety and reliability of residential electricity consumption.it is necessary to actively plan and modify the distribution network’s structure in the power grid,improve the quality of the distribution network,and optimize the planning of the distribution network,so that the network can be fully utilized to meet the needs of electricity consumption.In this paper,a distribution network grid planning algorithm based on the reliability of electricity consumption was completed using ant colony algorithm.For the distribution network structure planning of dual power sources,the parallel ant colony algorithm was used to prove that the premise of parallelism is the interactive process of ant colonies,and the dual power distribution network structure model is established based on the principle of the lowest cost.The artificial ants in the algorithm were compared with real ants in nature,and the basic steps and working principle of the ant colony optimization algorithm was studied with the help of the travelling salesman problem(TSP).Then,the limitations of the ant colony algorithm were analyzed,and an improvement strategy was proposed by using python for digital simulation.The results demonstrated the reliability of model-building and algorithm improvement.

Parallel discrete lion swarm optimization algorithm for solving traveling salesman problem

As a typical representative of the NP-complete problem, the traveling salesman problem(TSP) is widely utilized in computer networks, logistics distribution, and other fields. In this paper, a discrete lion swarm optimization(DLSO) algorithm is proposed to solve the TSP. Firstly, we introduce discrete coding and order crossover operators in DLSO. Secondly, we use the complete 2-opt(C2-opt) algorithm to enhance the local search ability.Then in order to enhance the efficiency of the algorithm, a parallel discrete lion swarm optimization(PDLSO) algorithm is proposed.The PDLSO has multiple populations, and each sub-population independently runs the DLSO algorithm in parallel. We use the ring topology to transfer information between sub-populations. Experiments on some benchmarks TSP problems show that the DLSO algorithm has a better accuracy than other algorithms, and the PDLSO algorithm can effectively shorten the running time.

Rule-based scheduling of multi-stage multi-product batch plants with parallel units

A novel rule-based model for multi-stage multi-product scheduling problem(MMSP)in batch plants with parallel units is proposed.The scheduling problem is decomposed into two sub-problems of order assignment and order sequencing.Firstly,hierarchical scheduling strategy is presented for solving the former sub-problem,where the multi-stage multi-product batch process is divided into multiple sequentially connected single process stages,and then the production of orders are arranged in each single stage by using forward order assignment strategy and backward order assignment strategy respectively according to the feature of scheduling objective.Line-up competition algorithm(LCA)is presented to find out optimal order sequence and order assignment rule,which can minimize total flow time or maximize total weighted process time.Computational results show that the proposed approach can obtain better solutions than those of the literature for all scheduling problems with more than 10 orders.Moreover,with the problem size increasing,the solutions obtained by the proposed approach are improved remarkably.The proposed approach has the potential to solve large size MMSP.

Research on the Optimal Parallel Algorithms of Broadcast-Class Problems

Speedup is considered as the criterion of determining whether a parallel algorithm is optimal. But broadcast-class problems, existing only on parallel computer system, have no sequential algorithms at all. Speedup standard becomes invalid here. Through this research on broadcast algorithms under several typical parallel computation models,a model-independent evaluation standard min C2 is developed, which can be not only used to determine an optimal broadcasting algorithm, but also normalized to apply to any parallel algorithm. As a new idea, min C2 will lead to a new way in this field.