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Abstract Community detection decomposes large‐scale, complex networks “optimally” into sets of smaller sub‐networks. It finds sub‐networks that have the least inter‐connections and the most intra‐connections. This article presents an efficient community detection algorithm that detects community structures in a weighted network by solving a multi‐objective optimization problem. The whale optimization algorithm is extended to enable it to handle multi‐objective optimization problems with discrete variables and to solve the problems on parallel processors. To this end, the population's positions are discretized using a transfer function that maps real variables to discrete variables, the initialization steps for the algorithm are modified to prevent generating unrealistic connections between variables, and the updating step of the algorithm is redefined to produce integer numbers. To identify the community configurations that are Pareto optimal, the non‐dominated sorting concept is adopted. The proposed algorithm is tested on the Tennessee Eastman process and several benchmark community‐detection problems. 

This article introduces a new system property called the closest feasible points (CFP) invariance to characterize systems with actuator saturation. Systems that possess this invariance property include diagonal matrices, completely decentralized (completely decoupled) linear dynamical systems, and dynamical systems with a nonsingular input-independent characteristic (decoupling) matrix that can be made diagonal with row or column rearrangements. However, a single-input single-output system may not possess this property. This system property has implications and applications in control, where actuator saturation is common. For example, when an actuator saturates, the closed-loop performance of a CFP non-invariant plant under a controller that is not a solution to a constrained optimal control problem, may degrade considerably. The definition of this property guides the derivation of optimal CFP non-invariance compensators that decrease the control performance degradation gracefully in CFP non-invariant plants. This work characterizes the plants for which clipping and direction preservation of controller outputs are optimal. 

Energy and electricity consumption is expected to increase in the foreseeable future. Concurrently, sustainability concerns of fossil‐based energy resources have motivated the use of renewable and reusable energy resources, and the use of more efficient energy‐converting and energy‐consuming systems. Consequently, for the past decade, there have been major theoretical and experimental advances in (1) energy generation from renewable and reusable resources and (2) energy‐consuming and energy‐converting devices. This review article focuses on the recent theoretical advances in renewable energy conversion devices such as photovoltaic and fuel cells, and in energy storage devices such as rechargeable batteries, flow batteries, and supercapacitors. Due to similar chemistry, electrochemistry, and physics of these systems, modeling similarities between different energy systems are highlighted. This review puts into perspective how first‐principles mathematical modeling has contributed to systematic advances in the optimal design, operation, and integration of these systems. © 2018 American Institute of Chemical EngineersAIChE J, 65: e16482 2019