Abstract: For the elevator group control system, this paper proposes a design and implementation method based on object-oriented analysis. Based on the elevator group system model, the layer compartmentalization and the relationship between the basic classes of the system are discussed. It is proved in practice that this method can significantly improve system performance indexes. Keywords: Elevator group control system, Elevator group model, Object-oriented 1 Introduction With the development of modern society and the progress of science and technology, many high-rise buildings and intelligent buildings have appeared in the world. Elevators, as a crucial, and sometimes the sole, mode of transportation within high-rise buildings, are increasingly used and complex. This has led to ever-higher demands on elevator system performance, with multiple elevators often operating simultaneously within the same building. Elevator Group Control Systems (EGCS) have emerged and developed precisely to meet this need. An EGCS is a system that optimizes the scheduling of multiple elevators within a single building. The goal of a group control system is to find the optimal scheduling scheme within a given elevator space, such as maximizing passenger capacity, minimizing passenger waiting time, and minimizing energy consumption. Regarding elevator group control, on the one hand, engineers are continuously improving the topology of the elevator group control system and the communication methods between elevators within the group to achieve high-speed, reliable scheduling control and communication connections. On the other hand, researchers both domestically and internationally are studying the statistical and dynamic characteristics of elevator traffic systems, utilizing artificial intelligence technologies such as expert systems, artificial neural networks, fuzzy neural networks, and immune algorithms to model elevator group control systems, aiming to establish more optimized control algorithms for managing elevator groups. Several methods have been proposed for the design and implementation of elevator group control systems. For example, distributed control methods [1], fuzzy neural network control methods [2], and fuzzy expert system control methods [3]. This paper proposes an object-oriented design and implementation method for elevator group control systems. 2 Introduction to Object-Oriented Methods 2.1 Characteristics of Object-Oriented Methods People understand the world in an "object-oriented" way. Problems in the objective world are composed of entities in the objective world and the relationships between these entities. We call the entities in the objective world objects in the problem space (problem domain), and complex objects can be composed of relatively simple objects in a certain way. Traditionally, people analyze and solve problems in a problem-oriented or process-oriented way. The analysis process does not care about the future design and implementation process. There is no direct connection between the problem model and the design model of the system. It is a top-down, functional decomposition method. The object-oriented method was proposed precisely to solve the problem that the process and method of understanding a system are inconsistent with the process and method of analyzing and designing a system. The term "object" refers to the real world and concrete or abstract transactions in the problem domain. In object-oriented methods, the problem is first decomposed into multiple objects, and then the objects are abstracted into data and a set of operations on the data set to obtain an abstract data type [4]. Objects generally have at least the following characteristics [4][5]: (1) Modularity. An object is an entity that can exist independently and exchange information with the outside world through a functional interface. (2) Inheritance and analogy. Objects at the next level in the same category should have some attributes of the objects at the previous level. (3) Dynamic connectivity. There should be a unified, convenient, and dynamic connection and message passing ability and mechanism between objects. (4) Maintainability. The implementation details of the object's functions are hidden inside the object. Therefore, the improvement or modification of the object's functions will not be passed to the outside of the object, which enhances the maintainability of the entire system. 2.2 When dealing with complex problem domains or system tasks, object-oriented analysis methods typically consider abstraction, encapsulation, inheritance, association, communication with messages, organization method, scale, and categories of behavior. Object-oriented methods can be expressed as: Object-oriented method = Object + Class + Inheritance + Message Communication. Object-oriented analysis is based on the concepts of information simulation (entity-relationship diagrams and semantic data types) and object-oriented programming languages, as shown in Figure 1 [5]. [align=center] Figure 1 Formation of Object-Oriented Analysis[/align] Object-oriented analysis methods draw upon concepts such as attributes, relationships, structures, and the representation of objects as instances of certain things in the problem domain from information simulation; they also draw upon concepts such as encapsulation of attributes and methods, attributes and methods as an inseparable whole, classification structures, and inheritance from object-oriented programming languages. Object-oriented analysis methods directly map the problem domain into a model. In this paper, we map it into a group-controlled elevator operation model. 3. Application of Object-Oriented Methods in Elevator Group Control System Design 3.1 Analysis of Elevator Group Control System Elevator group control systems are complex nonlinear dynamic systems, exhibiting discreteness and randomness in time and space. To better study elevator group control technology and verify the operational effectiveness of group control algorithms, a mathematical model of the elevator group control system should first be established. Various theories and methods can be applied to establish elevator group control models. Based on simulating elevator motion behavior using a cellular automata model, this paper establishes a complete elevator group control system model, as shown in Figure 2. [align=center] Figure 2 Elevator Group Control Model[/align] 3.2 Object-Oriented Implementation of Elevator Group Control System The model shown in Figure 2 is analyzed using the object-oriented analysis (OOA) method proposed by Coad/Yourdon, and the program is written using the Visual C++ computer programming language. Based on the object-oriented analysis principles stated above, the entire model is divided into five layers: class and object layer, attribute layer, service layer, structure layer, and theme layer. The class and object layer describes the basic class modules of the elevator group control system to be developed; the attribute layer defines the attributes of classes and objects; the service layer defines the services of objects, i.e., the operations of classes and their message connections. Figure 3 shows the basic class module relationship diagram of the elevator group control system model. [align=center] Figure 3 Class module relationship diagram of the elevator group control system model[/align] Figure 3 specifically describes the attributes, services, and relationships between the five basic classes in the system model. The various class modules in the model communicate through message passing. The call signal generated by the passenger (PASSENGER) button is stored in the call signal buffer queue (CALLQUEUE). The hall call signals in this queue are sent to the group control algorithm module (GROUP-CONTROL) for dispatch calculation. Successful dispatch commands are placed in the dispatch queue (ALLOCATION), and the dispatched elevator (ELEVATOR) responds to the call. After completing the call command, the elevator records the information for that stop. Call signals that have not yet been dispatched, as well as call signals that failed to be dispatched due to reasons such as a full car or group control strategy, are still stored in the buffer queue, waiting for the next elevator dispatch calculation. Car call signals do not require group control calculations; they are directly placed into the corresponding elevator dispatch queue according to logical relationships. The simulation of elevator behavior by the cellular automata model is jointly completed in the ALLOCATION and ELEVATOR classes. 4. Actual Operation Results of the Group Control Algorithm Table 1 below compares several sets of data obtained during actual operation. Table 1 Comparison of Group Control Operation Effects From the table, we can see that the group control algorithm analyzed and implemented using the object-oriented method has good results. All evaluation indicators of the group control system have been significantly improved, with the maximum waiting time and long waiting rate reduced to more than half of the original. 5. Conclusion For the problem domain of elevator group control systems, which are complex nonlinear dynamic systems with discrete and random characteristics in time and space, this paper proposes an analysis and implementation method based on object-oriented analysis. Based on the proposed elevator group control model, the group control system is divided into 5 levels, and the basic class relationship diagram of the system model is given. The operation results show that the elevator group control system implemented using the object-oriented analysis method has good practical application effects. The innovation of this paper lies in the fact that, based on the cellular automata model of elevator group systems, the author presents and analyzes the basic classes of elevator group systems and the relationships between them. References: [1] Liu Guocai et al., Distributed control technology of elevators, Measurement and Control Technology, Vol. 18, No. 6, 1999; [2] ChangBum Kim, Design and Implementation of a Fuzzy Elevator Group Control System, IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART A: SYSTEMS AND HUMANS, VOL. 28, NO. 3, MAY 1998; [3] T. Ishikawa A. Miyauchi and M. 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