Erratum to “Single-machine scheduling problems with both deteriorating jobs and learning effects” [Appl. Math. Modell. 34 (2010) 2831–2839]

The aim of this paper is to show by counterexamples that Theorems 3–10 and Corollaries 2–5 in Wang et al. [Appl. Math. Model. 34 (2010) 2831–2839] are incorrect.     

A hybrid of genetic algorithm and particle swarm optimization for solving bi-level linear programming problem – A case study on supply chain model

The main goal of supply chain management is to coordinate and collaborate the supply chain partners seamlessly. On the other hand, bi-level linear programming is a technique for modeling decentralized decision. It consists of the upper level and lower level objectives. Thus, this paper intends to apply bi-level linear programming to supply chain distribution problem and develop an efficient method based on hybrid of genetic algorithm (GA) and particle swarm optimization (PSO). The performance of the proposed method is ascertained by comparing the results with GA and PSO using four problems in the literature and a supply chain distribution model.     

Erratum to “Single machine past-sequence-dependent setup times scheduling with general position-dependent and time-dependent learning effects” [Appl. Math. Modell. 35 (2011) 1388–1395]

The aim of this paper is to show by a counterexample that Theorem 7 and Corollary 8 in Wang and Li [Appl. Math. Modell. 35 (2011) 1388–1395.] are incorrect.     

Erratum to “Fuzzy rough set model on two different universes and its application” [Appl. Math. Model. 35 (4) (2011) 1798–1809]

The aim of this paper is to correct two mistakes in [Appl. Math. Model. 35 (4) (2011) 1798–1809], which are: one of the properties of fuzzy rough set between two different universes and the definition of the upper approximation with the property for degree fuzzy rough set between two different universes.     

Corrigendum to “The envelope theorem for multiobjective convex programming via contingent derivatives” [J. Math. Anal. Appl. 372 (1) (2010) 197–207]

The aim of this note is to formulate an envelope theorem for vector convex programs. This version corrects an earlier work, “The envelope theorem for multiobjective convex programming via contingent derivatives” by Jiménez Guerra et al. (2010) [3]. We first propose a necessary and sufficient condition allowing to restate the main result proved in the alluded paper. Second, we introduce a new Lagrange multiplier in order to obtain an envelope theorem avoiding the aforementioned error.     

Comments on: “A family of derivative-free conjugate gradient methods for large-scale nonlinear systems of equations” [J. Comput. Appl. Math. 224 (2009) 11–19]

In this note a simple counter example shows that the proof of Lemma 3.3 in [1, W. Cheng, Y. Xiao and Q. Hu, A family of derivative-free conjugate gradient methods for large-scale nonlinear systems of equations, J. Comput. Appl. Math. 224 (2009) 11–19] is not correct, which implies that Lemma 3.2 in [1] is not enough to ensure Lemma 3.3 in [1]. A new proof is given, which leads to a stronger result than Lemma 3.2 in [1]. And this result not only guarantees that Lemma 3.3 in [1] holds, but also improves the corresponding global convergence Theorem 3.1 in [1].