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Flexible job-shop scheduling problem (FJSP) is an extended traditional job-shop scheduling problem, which more approximates to practical scheduling problems. This paper presents a multi-objective genetic algorithm (MOGA) based on immune and entropy principle to solve the multi-objective FJSP. In this improved MOGA, the fitness scheme based on Pareto-optimality is applied, and the immune and entropy principle is used to keep the diversity of individuals and overcome the problem of premature convergence. Efficient crossover and mutation operators are proposed to adapt to the special chromosome structure. The proposed algorithm is evaluated on some representative instances, and the comparison with other approaches in the latest papers validates the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

The paper considers the problems of scheduling n jobs that are released over time on a machine in order to optimize one or more objectives. The problems are dynamic single-machine scheduling problems (DSMSPs) with job release dates and needed to be solved urgently because they exist widely in practical production environment. Gene expression programming-based scheduling rules constructor (GEPSRC) was proposed to construct effective scheduling rules (SRs) for DSMSPs with job release dates automatically. In GEPSRC, Gene Expression Programming (GEP) worked as a heuristic search to search the space of SRs. Many experiments were conducted, and comparisons were made between GEPSRC and some previous methods. The results showed that GEPSRC achieved significant improvement. [ABSTRACT FROM AUTHOR]

This paper is concerned about the sequencing problems in pull production systems which are composed of one mixed-model assembly line and one flexible fabrication flow line with limited intermediate buffers. Two objectives are considered simultaneously: minimizing the total variation in parts consumption in the assembly line and minimizing the makespan in the fabrication line. The mathematical models are presented. Since the problem is Non-deterministic Polynomial-hard (NP-hard), a multiobjective genetic algorithm is proposed for solving the models, in which a method to generate the production sequence for the fabrication line from the production sequence for the assembly line is put forward, and Pareto ranking method and sharing function method are employed to evaluate the individuals' fitness. The feasibility and efficiency of the multiobjective genetic algorithm is shown by computational comparison with an adaptive genetic algorithm and a multiobjective simulated annealing. [ABSTRACT FROM AUTHOR]

Glucocorticoids exert both anabolic and catabolic effects on bone. Previously, we reported that endogenous glucocorticoids control mesenchymal lineage commitment and osteoblastogenesis through regulation of Wnt signaling in osteoblasts. Here, we investigated the effects of glucocorticoids on Wnt expression in mature osteoblasts. Mature osteoblasts and their immature progenitors were separately isolated from Col2.3-GFP transgenic mice in which mature osteoblasts are identifiable through GFP expression. mRNA levels of Wnt2, Wnt2b, Wnt4, Wnt5a, Wnt10b, and Wnt11 were 4- to 12-fold higher in osteoblasts compared to their progenitors ( P < 0.05). Expression of Wnt7b and Wnt10b in osteoblasts was modulated by corticosterone (CS), in a biphasic fashion with 3- to 3.5-fold upregulation at 10 nM CS ( P < 0.01) and 50% downregulation at 100 nM CS ( P < 0.05). CS 100 nM also increased expression of the Wnt inhibitors sFRP-1 and DKK-1 two- to threefold ( P < 0.05). We conclude that the contrasting anabolic and catabolic effects of glucocorticoids on bone are, at least in part, mediated through the regulation of Wnt expression and its inhibitors in mature osteoblasts. [ABSTRACT FROM AUTHOR]

In order to reduce manufacturing cost and to improve the operational efficiency, some factories in the sheet-metal-related manufacturing industry centralize the production and management of sheet metal cutting. To support the centralized mass manufacturing paradigm, this paper presents an integrated manufacturing information system to achieve the high utilization of raw sheet material, lower the manufacturing cost, as well as to improve the operational efficiency and production management. The system architecture and some key technologies to implement this system are investigated, based on which, the whole information system is developed. This system integrates the functions of sheet metal part modeling and unfolding, nesting planning, automatic and interactive nesting, cutting process planning, NC-programming, off-line processing simulation and on-line monitoring. The system has been successfully utilized in industry, and an example of its application is described in the paper. [ABSTRACT FROM AUTHOR]