A petrochemical smart factory is a green, efficient, safe and sustainable modern factory that combines cutting-edge information and communication technology with petrochemical advanced technology and equipment. A Cyber-physical System (CPS) is the infrastructure of a petrochemical smart factory. Based on the future challenges of the petrochemical industry, this paper proposes the definition, connotation and framework of a petrochemical CPS and constructs a CPS system at the enterprise, unit and field levels, respectively. Furthermore, the paper provides theoretical support and implementation reference of a CPS in the petrochemical industry and other industries by investigating the construction practice of a multi-level CPS in the China Petrochemical Corporation (SINOPEC).

供应链中决策是分层的。其中，战略决策涉及供应链网络结构的长期规划，战术决策是决策物料生产和配送的中期计划，而运作决策则和实施制造的日计划相关。这三个规划过程是独立进行的，它们之间的信息交互非常少。本文提出了一种多层决策的网络表达方式，并以最大化决策网络各结点总体效益为目标进行分析和优化。关于决策网络中各组件的研究已经取得了一些成果。本文对关于战略决策模型、中期计划模型和调度模型的研究进行了综述；对包括大规模模型、多目标优化、双层规划、分解等相关的协调机制进行了分析；最后，对供应链管理的多层决策的整体集成带来的挑战进行了总结。

Boosting the resilience of power systems is a core requirement of smart grids. In fact, resilience enhancement is crucial to all critical infrastructure systems. In this study, we review the current research on system resilience enhancement within and beyond smart grids. In addition, we elaborate on resilience definition and resilience quantification and discuss several challenges and opportunities for system resilience enhancement. This study aims to deepen our understanding of the concept of resilience and develop a wide perspective on enhancing the system resilience for critical infrastructures.

L♮-凸性是离散凸分析的核心内容，近年来在运作管理研究中受到普遍关注，它能够为有效计算求解提供结构性的最优策略。本文对L♮-凸性的关键特征进行了综述，并对运作应用中网格规划的近期相关结果进行了总结。本文还建立了u-微分单调性和L♮-凸性的关系进行了分析。以易腐物库存模型和考虑随机容量的库存运输集成控制模型为例，对如何应用L♮-凸性相关技术进行了说明。

本文对随机制造和服务系统的解析方法进行了研究综述。基于运营细节的范围和层次，我们深入研究了随机系统的微观、中观和宏观模型，统一随机模型理论。针对每种模型，我们着重分析其优势和缺陷，以及适用情况。考虑到阶段分布的服务时间和马尔科夫到达过程，微观模型是基于拟生灭过程；该模型适用于在服务器（生产设备）数量相对较少的情况下，对生产系统中的细节运作进行建模。相比之下，在交通拥挤情形中，中观和宏观模型则分别基于泛函中心极限定理和泛函强数定律。这些高层次模型适用于具有许多服务器（如呼叫中心或大型服务网络）的大型服务系统建模。本研究综述将有助于从业人员选择适当的建模层次，以提高他们对制造或服务系统的动态行为的理解，从而确保可以设计出改善系统性能的最佳方案。此外，从事制造与物流的运营分析和优化的研究人员也将受益于本文。

In practice, an energy consumer often consists of a set of residential or commercial buildings, with individual units that are expected to cooperate to achieve overall optimization under modern electricity operations, such as time-of-use price. Global utility is decomposed to the payoff of each player, and each game is played over a prediction horizon through the design of a series of sliding window games by treating each building as a player. During the games, a distributed learning algorithm based on game theory is proposed such that each building learns to play a part of the global optimum through state transition. The proposed scheme is applied to a case study of three buildings to demonstrate its effectiveness.

As part of China’s “the Belt and Road” strategy, China Railway Express provides alternative shipping routes and transportation modes from Asia to Europe and creates new opportunities for intermodal transportation in the shipping industry. A time–distance-based cost (time cost) function was proposed to compare China Railway Express with traditional transportation modes. Time cost was related to different types of cargoes, which exhibit distinct sensitivity to time. Using the proposed cost function as basis, we identified the cost indifference area where total costs are equal. Further analysis was performed for selecting the transportation mode and supply area for a specific cargo. This study provides various parties, such as business owners, the government, and the shipping industry, with many valuable insights.

An increasing number of novel and highly specialized computer-aided decision-making technologies for short-term production scheduling in oil refineries has emerged and evolved over the past two decades, thereby encouraging refiners to permanently rethink the way the refining business is operated and managed. In this report, we discuss the key lessons learned from one of the pioneering, yet daring, enterprise-wide programs entirely implemented in an energy company devoted to developing and implementing an advanced refinery production scheduling (RPS) technology, i.e., the RPS system of Petrobras. Apart from mathematical and information technology issues, the long-term sustainability of a successful RPS project is, we argue, the outcome of a virtuous cycle grounded on permanent actions devoted to improving technical education inside the organization, reinspecting organizational cultures and operational paradigms, and developing working processes.

This study aims to solve a typical long-term strategic decision problem on supply chain network design with consideration to uncertain demands. Existing methods for these problems are either deterministic or limited in scale. We analyze the impact of uncertainty on demand based on actual large data from industrial companies. Deterministic equivalent model with nonanticipativity constraints, branch-and-fix coordination, sample average approximation (SAA) with Bayesian bootstrap, and Latin hypercube sampling were adopted to analyze stochastic demands. A computational study of supply chain network with front-ends in Europe and back-ends in Asia is presented to highlight the importance of stochastic factors in these problems and the efficiency of our proposed solution approach.

Petrochemical industry plays an important role in the development of the national economy. Purified terephthalic acid (PTA) is one of the most important intermediate raw materials in the petrochemical and chemical fiber industries. PTA production has two parts: p-xylene (PX) oxidation process and crude terephthalic acid (CTA) hydropurification process. The CTA hydropurification process is used to reduce impurities, such as 4-carboxybenzaldehyde, which is produced by a side reaction in the PX oxidation process and is harmful to the polyester industry. From the safety and economic viewpoints, monitoring this process is necessary. Four main faults of this process are analyzed in this study. The common process monitoring methods always use T ² and SPE statistic as control limits. However, the traditional methods do not fully consider the economic viewpoint. In this study, a new economic control chart design method based on the differential evolution (DE) algorithm is developed. The DE algorithm transforms the economic control chart design problem to an optimization problem and is an excellent solution to such problem. Case studies of the main faults of the hydropurification process indicate that the proposed method can achieve minimum profit loss. This method is useful in economic control chart design and can provide guidance for the petrochemical industry.

The global production of bio-based chemical products, particularly biofuel products, has tremendously increased over the last decade. Driven largely by a new legislation, this increase has generated the commercialization of new products and processes. Unfortunately, alongside these developments were a significant number of accidents and explosions at biofuel facilities, entailing property damage, injury, and even deaths. The aim of this current study is to draw attention to incidents that occurred in biofuel facilities and clarify the misconceptions that cause people to ignore safety in bio-refineries. A process hazard analysis (PHA) method, namely the hazard and operability study (HAZOP), is first used in biofuel production. This method is an ethanol distillation and dehydration process. Through the HAZOP analysis, 36 recommended action items are proposed, and all recommendations are accepted. The case study reveals that potential high-level risks exist in the current biofuel process design and operating procedures, and these risks can be better controlled if they can be previously identified.

This study addresses the problem of two-stage scheduling on batch and single machines with limited waiting time constraint; thus, the makespan is minimized. A mixed-integer linear programming model is proposed for this problem. Three tight lower bounds and a heuristic algorithm are developed. The worst-case performance of the proposed algorithm is discussed. A hybrid differential evolution algorithm is also developed to improve the solution quantity. Numerical results show that the hybrid algorithm is capable of obtaining high-quality solutions and exhibits a competitive performance