# Special Issue on Modeling, Simulation, Operation and Control of Discrete Event Systems
###### Abstract  
Information and computer technologies provide the spur to burgeoning man-made, highly automated systems. Nowadays, discrete event systems (DES), as a natural abstraction of various contemporary technological applications, include intelligent urban traffic systems, automated flexible manufacturing systems, computer networks, communication protocols, logistic systems, monitoring and control of large buildings, scientific and business workflows, distributed databases, and concurrent software systems. Their modeling, simulation, operation, scheduling and control are the primary issues to be investigated. It is of paramount significance to develop novel formal frameworks, analysis techniques, design tools, testing methods, and systematic control and optimization procedures for these kinds of man-made, highly complex systems. This is critical for their development and survivability [1, 2, 3, 4, 5, 6]. Focusing on supervisory control, deadlock analysis, scheduling, resource management, performance evaluation, system identification, fault diagnosis, and performance evaluation, as well as pertinent problems of DES, this special issue aims to make a timely collection of recent advances in the area. There were 77 manuscripts submitted to this special issue, and 19 papers were finally accepted for publication. The acceptance rate was 24.6%. The first paper [7], authored by [PERSON] and [PERSON], investigates the input-output finite time stabilization of time-varying impulsive positive hybrid systems based on finite state machines through the mode-dependent average dwell time technique. An output feedback controller is proposed that can stabilize non-autonomous hybrid systems by formulating the considered problem as a linear program. The second paper [8], authored by [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], and [PERSON], is concerned with the efficiency improvement of multi-agent simulation. To address the problem of resynchronization interval selection and cyclic dependency, this paper presents a lookahead behavior model where a minimal safe time window is used to predict the interactions among implicit models. Consequently, the resynchronization interval can be efficiently determined. The third paper [9], authored by [PERSON], proposes a heuristic decision-making approach for an NP-hard scheduling problem based on an algebraic-logical meta-model. By constructing an acceptable solution only, it significantly reduces the calculation cost. A general algorithm is developed and applied to the scheduling problems of unrelated parallel machines with a deadline and machine setup time dependent on the process state. The fourth paper [10], authored by [PERSON], [PERSON], and [PERSON], deals with discrete event system simulation, aiming to improve simulation efficiency by using a multi-fidelity modeling framework, while keeping simulation accuracy loss minimized. A number of novel concepts, such as an interest region, a fidelity change condition, and a selection model, are defined and integrated into the framework. Motivated by the effectiveness of heuristic rules, the fifth paper [11], authored by [PERSON], [PERSON], [PERSON], and [PERSON], reports a dynamic scheduling strategy for semiconductor manufacturing lines by considering various factors and constraints such as make-span and equipment efficiency that are stringently tied to system performance. The proposed method dynamically computes a composite dispatching rule that can be used to optimize production performance. Proposed in the sixth paper [12], by [PERSON], [PERSON] and [PERSON], is an optimization method for single artillery unit fire scheduling problems. Taking the threat level of an enemy target to be an uncertain parameter, a robust optimization model is developed, minimizing the total enemy threat to friendly forces. Numerical experiments are conducted to validate the performance of the presented solution method.