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Simultaneous optimization of service cost and waiting cost in service systems

机译：同时优化服务成本和服务系统等待成本

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摘要

The operational cost of service systems consists of service costs and waiting costs. Service cost is associated with the employment of service-providing personnel, while the waiting cost is associated with the customers having to wait for the service. The two categories of costs are mutually opposed, so that a decrease in one causes an increase in the other and vice-versa. In this paper, we cast the problem as a multi-objective optimization problem and use the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm to minimize the two categories of costs simultaneously. MOPSO is a fairly recent swarm intelligence meta-heuristic algorithm known for its simplicity in programming and its rapid convergence. The multi-objective optimization procedure is illustrated with the example of a practical service system. MOPSO produces a near-perfect Pareto front for the two conflicting objective functions in the practical service system.
机译：服务系统的运营成本包括服务成本和等待费用。服务成本与服务提供人员的就业有关，而等待成本与不得不等待服务的客户有关。两种类别的成本是相互反对的，因此减少一个导致另一个导致另一类增加，反之亦然。在本文中，我们将问题作为多目标优化问题，并使用多目标粒子群优化（MOPSO）算法同时最小化两类成本。 MOPSO是一种相当于最近的群体智能元算法，以其简单的编程及其快速收敛而闻名。利用实际服务系统的示例说明了多目标优化过程。 MOPSO为实际服务系统中的两个冲突的客观函数产生了近乎完美的帕累托前线。

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