60 research outputs found
Charge Scheduling of an Energy Storage System under Time-of-use Pricing and a Demand Charge
A real-coded genetic algorithm is used to schedule the charging of an energy
storage system (ESS), operated in tandem with renewable power by an electricity
consumer who is subject to time-of-use pricing and a demand charge. Simulations
based on load and generation profiles of typical residential customers show
that an ESS scheduled by our algorithm can reduce electricity costs by
approximately 17%, compared to a system without an ESS, and by 8% compared to a
scheduling algorithm based on net power.Comment: 13 pages, 2 figures, 5 table
Accounting for Recent Changes of Gain in Dealing with Ties in Iterative Methods for Circuit Partitioning
In iterative methods for partitioning circuits, there is often a choice among several
modules which will all produce the largest available reduction in cut size if they are moved
between subsets in the partition. This choice, which is usually made by popping modules off
a stack, has been shown to have a considerable impact on performance. By considering the
most recent change in the potential reduction in cut size associated with moving each module
between subsets, the performance of this LIFO (last-in first-out) approach can be significantly
improved
A Memetic Lagrangian Heuristic for the 0-1 Multidimensional Knapsack Problem
We present a new evolutionary algorithm to solve the 0-1 multidimensional knapsack problem.
We tackle the problem using duality concept, differently from traditional approaches.
Our method is based on Lagrangian relaxation.
Lagrange multipliers transform the problem, keeping the optimality as well as decreasing the complexity.
However, it is not easy to find Lagrange multipliers nearest to the capacity constraints of the problem.
Through empirical investigation of Lagrangian space, we can see the
potentiality of using a memetic algorithm.
So we use a memetic algorithm to find the optimal Lagrange multipliers.
We show the efficiency of the proposed method by the experiments on well-known benchmark data
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