Scheduling Practical Generating System Using an Improved Bacterial Swarm Optimization
نویسندگان
چکیده
Original scientific paper This paper offers an improved technique namely, Quorum sensing based Bacterial Swarm Optimization (QBSO) technique to solve Practical Dynamic Economic Dispatch (PDED) problem. Quorum sensing is the communication signalling mechanism that permits the bacteria to organize the collective behaviour. The enhanced QBSO method improves the exploration capability of bacterial swarm. The practicability of the proposed method is tested on standard 10 generating unit system and the public practical south Indian 20 thermal generating system with recorded load demand profiles. The enhanced technique increases the operational speed of scheduling and reduces the generating cost of standard system and the thermal generating units owned by Tamilnadu Generation and Distribution Corporation Limited (TANGEDCO). The presented technique outperforms when compared with conventional bacterial swarm optimization technique and some recently published methods.
منابع مشابه
Task Scheduling Using Particle Swarm Optimization Algorithm with a Selection Guide and a Measure of Uniformity for Computational Grids
In this paper, we proposed an algorithm for solving the problem of task scheduling using particle swarm optimization algorithm, with changes in the Selection and removing the guide and also using the technique to get away from the bad, to move away from local extreme and diversity. Scheduling algorithms play an important role in grid computing, parallel tasks Scheduling and sending them to ...
متن کاملTask Scheduling Using Particle Swarm Optimization Algorithm with a Selection Guide and a Measure of Uniformity for Computational Grids
In this paper, we proposed an algorithm for solving the problem of task scheduling using particle swarm optimization algorithm, with changes in the Selection and removing the guide and also using the technique to get away from the bad, to move away from local extreme and diversity. Scheduling algorithms play an important role in grid computing, parallel tasks Scheduling and sending them to ...
متن کاملA Coevolutionary Bacterial Foraging Model Using PSO in Job- Shop Scheduling Environments
The optimization of job-shop scheduling is very important because of its theoretical and practical significance. In this paper, a computationally effective approach of combining bacterial foraging strategy with particle swarm optimization for solving the minimum makespan problem of job shop scheduling is proposed. In the artificial bacterial foraging system, a novel chemotactic model is designe...
متن کاملParticle swarm optimization for minimizing total earliness/tardiness costs of two-stage assembly flowshop scheduling problem in a batched delivery system
This paper considers a two-stage assembly flow shop scheduling problem. When all parts of each product are completed in the first stage, they are assembled into a final product on an assembly machine in the second stage. In order to reduce the delivery cost, completed products can be held until completion of some other products to be delivered in a same batch. The proposed problem addresses sch...
متن کاملOptimization of grid independent diesel-based hybrid system for power generation using improved particle swarm optimization algorithm
The power supply of remote sites and applications at minimal cost and with low emissions is an important issue when discussing future energy concepts. This paper presents modeling and optimization of a photovoltaic (PV)/wind/diesel system with batteries storage for electrification to an off-grid remote area located in Rafsanjan, Iran. For this location, different hybrid systems are studied and ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2016