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ABSTRACT-The car dispatching problem in an elevator group consists of assigning cars to the hall calls at the same time that car call are served. The problem needs to coordinate the movements of individual cars with the objective of operating efficiently the whole group. In this paper, we propose an elevator group control system based on a genetic algorithm which makes use of a novel fitness function to evaluate the individuals. The fitness function allows a quick execution of the algorithm. Tests are provided for various types of high-rise buildings to assess the elevator service performance. Comparative simulations show that our genetic algorithm outperforms traditional conventional algorithms developed in the industry. It is important to note that the algorithm is quickly evaluated allowing a real-life implementation.

The supply chain has become a key element of increasing the productivity and competitiveness of companies. To achieve this, it is essential to implement a strategy based on the use of technologies, which depends on knowledge of the scope and impact of logistics technologies. Therefore, this article aims to identify the main technologies supporting logistics management and supply chain processes to establish their functionality, scope, and impacts. For this, conventional technologies and technologies framed by the concept of Industry 4.0 that allow the implementation of Logistics 4.0 in companies are analyzed. As a result of searching databases such as Scopus, Web of Science, and Science Direct, we provide an analysis of 18 technologies focusing on their definition, scope, and the logistics processes involved. This study concludes that technologies in logistics management allow for a reduction in total costs, improve collaboration with suppliers and customers, increase the visibility and traceability of products and information, and support decision-making for all agents in the supply chain, including the final consumer.

High-rise buildings with a considerable number of elevators represent a major logistical problem concerning saving space and time for economic reasons. For this reason, complex elevator group control systems (EGCSs) are developed in order to manage elevators properly. In this paper, the first entirely dynamic fuzzy logic EGCS to dispatch landing calls so as to minimize waiting time is proposed. The fuzzy logic design described here not only constitutes an innovative solution that outperforms usual dispatchers but also an easy, cheap, feasible, and reliable solution, which is able to be implemented. This is achieved by an intelligent design that joins together the simplicity of fuzzy design with the performance of the most sophisticated controllers by considering the impact of landing call reallocations within the system waiting time scale based on the assessment of the landing call relative/absolute waiting time balancing.

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Abstract. The efficient performance of elevator group system controllers becomes a first order necessity when the buildings have a high utilisation ratio of the elevators, such as in professional buildings. We present a genetic algorithm that is compared with traditional controller algorithms in industry applications. An ARENA simulation scenario is created during heavy lunchpeak traffic conditions. The results allow us to affirm that our genetic algorithm reaches a better performance attending to the system waiting times than THV algorithm.

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