Comments on “Robust state estimation for uncertain discrete-time stochastic systems with missing measurements” [Automatica 47 (2011) 1520–1524]

We show that some results presented in the aforementioned article are rather limited. One of the major restrictions on applicability of the obtained results is the ergodic requirement on the received plant output measurements, which is generally not satisfied by a time-varying system. Another major restriction is that the comparisons are not appropriate for its numerical simulations, that is, using the state estimation results of an estimator that utilizing current and past observations to compare with those of a one-step state predictor is not appropriate. To evaluate the filter performances objectively, we do a numerical simulation with the robust state estimator and the well-known Kalman filter that does not take either parametric errors or random measurement loss into account; and the simulation results show that there is no significant difference in filtering performance between these two estimators.     

Erratum to “Solving the multi-buyer joint replenishment problem with the RAND method” [Comput. Indus. Eng. 46 (2004) 755–762]

A heuristic called RAND was used by Q. Li [Li, Q., 2004. Solving the multi-buyer joint replenishment problem with the RAND method. Computers & Industrial Engineering, 46, 755–762] to solve the multi-buyer joint replenishment problem. In this paper, errors made in the proposed RAND procedure of Q. Li (2004) are rectified. Furthermore, modifications to the proposed RAND procedure are also given.     

Corrigendum to “Uniform constant-depth threshold circuits for division and iterated multiplication” [J. Comput. System Sci. 65 (4) (2002) 695–716]

In this corrigendum, we retract part of our Corollary 6.6, which was presented as an immediate and obvious consequence of our main theorem, which showed that division lies in Dlogtime-uniform TC⁰${\mathrm{TC}}^0$.     

Comment on “On LMI conditions to design observer-based controllers for linear systems with parameter uncertainties [Automatica 49 (2013) 3700–3704]”

The main objective of this note is to point out the fatal error in a recent paper (Automatica 49 (2013) 3700–3704) and present a correct result. One numerical example is also given in order to show the nonsuperiority of the aforementioned paper to the existing literatures.     

Corrigendum to “Note on covering monotone orthogonal polygons” [Inf. Process. Lett. 104(6) (2007) 220–227]

Recently, a gap in Step 4 of Algorithm Sweep3 (and thus in Step 4 of Algorithm Minimum-Guard-Cover) presented in our paper entitled “Note on covering monotone orthogonal polygons with star-shaped polygons”, which appeared in Information Processing Letters 104(6), pp. 220–227 (2007), was pointed out by Leonidas Palios. In this corrigendum, we fix this gap and update the correctness proof in accordance with the new version of the algorithm.     

Comments on “An improved model for vehicle routing problem with time constraint based on genetic algorithm” [Comput. Ind. Eng. 42 (2002) 361–369]

An improved model for vehicle routing problem proposed by Heung-Suk Hwang (2002) was recently published in Computer & Industrial Engineering Journal to solve the time constraint vehicle routing problem based on improved genetic algorithm. In this work, comments are given to the published paper of Heung-Suk Hwang (2002). And they centralize on the example of improved mutation operator and the problem formulation. The suggested modifications are also provided in this work.     

Erratum to “A stochastic controller for a scalar linear system with additive Cauchy noise” [Automatica 50(1) (2014) 114–127]

A stochastic control scheme is developed for scalar, discrete-time, and linear-dynamic systems driven by Cauchy distributed process and measurement noises. When addressing the optimal control problem for such systems, the standard quadratic cost criteria cannot be used. In this study we introduce a new objective function that is functionally similar to the Cauchy probability density function. The performance index, defined as the expectation of this objective function with respect to the Cauchy densities, exists. The dynamic programming solution to the fixed and finite horizon optimal control problem that uses this performance index appears to be intractable. Therefore, a moving horizon optimal model predictive control problem is implemented, for which the conditional expected value of the objective function and its gradients can be computed in closed   form and without assumptions such as certainty equivalence. Numerical results are shown for this m$m$-step model predictive optimal controller and compared to a similar, Linear–Exponential–Gaussian model predictive controller. An essential difference between the Cauchy and Gaussian controllers when applied to a system with Cauchy noises is that, while the Gaussian controller is linear and reacts strongly to all noise pulses, the Cauchy controller can differentiate between measurement and process noise pulses by ignoring the former while responding to the latter. This property of the Cauchy controller occurs when an impulsive measurement noise is more likely than an impulsive process noise. The Cauchy and Gaussian controllers react similarly when applied to a system with Gaussian noises, demonstrating the robustness of the proposed control scheme.     

Erratum to “Finding the most efficient DMUs in DEA: An improved integrated model” [Comput. Indus. Eng. 52 (2007) 71–77]

There are two errors existing in “Finding the most efficient DMUs in DEA: An improved integrated model” (Amin & Toloo, 2007), one exists in the process of proving the theorem that “Theorem:model (3) is feasible (p. 75)”, while the other is that model (3) and model (4) are incorrectly built.     

Erratum to “A discrete colonial competitive algorithm for hybrid flowshop scheduling to minimize earliness and quadric tardiness penalties” [Expert Syst. Appl. 38 (2011) 14490–14498]

In this note, we point out that the mixed integer programming model of a hybrid flowshop scheduling problems presented by Behnamian and Zandieh [Expert Syst. Appl. 38 (2011) 14490–14498] is incorrect. We also point out that some responses from the authors are mistake.