optimization algorithm

An integer black-box optimization model for repairable spare parts management

Spare parts management affects significantly costs and service level for supply chains. This paper deals with an inventory management problem for multi-item repairable systems via a systemic perspective based on a new efficient integer black-box optimization model. With respect to the traditionally used marginal allocation that considers items individually, the proposed black-box optimization model is a holistic approach in the fact that it exploits relationships among items.

Short-term electricity price and load forecasting in isolated power grids based on composite neural network and gravitational search optimization algorithm

Electricity price forecasting is a key aspect for market participants to maximize their economic efficiency in deregulated markets. Nevertheless, due to its non-linearity and non-stationarity, the trend of the price is usually complicated to predict. On the other hand, the accuracy of short-term electricity price and load forecasting is fundamental for an efficient management of electric systems. An accurate prediction can benefit future plans and economic operations of the power systems’ operators.

Assessment of the worthwhileness of efficient driving in railway systems with high-receptivity power supplies

Eco-driving is one of the most important strategies for significantly reducing the energy consumption of railways with low investments. It consists of designing a way of driving a train to fulfil a target running time, consuming the minimum amount of energy. Most eco-driving energy savings come from the substitution of some braking periods with coasting periods. Nowadays, modern trains can use regenerative braking to recover the kinetic energy during deceleration phases.

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