Analysis of Opportunities and Challenges for R&D Management and the Role of the R&D Society for its Improvement – A Case Study in Iran

Research and Development (R&D) management in Iran is faced to many barriers and obstacles, in which R&D units are considered as the basic core of the product development and innovation. Due to structural shortcomings, a great number of organizations and industries have not been able to find their actual status. There are about different 1141 R&D units with a dispersion pattern in Iran. This paper considers and analyzes the R&D case study in one of the provinces located in the north part of Iran in order to enhance the potential R&D activities in respect with the industrialized areas and zones. In this province, there are about 2504 industrial units of which there are only 44 R&D units certified by the state government. However, there are limit numbers of these R&D units that are extensively active. This paper also addresses the current status in respect with the R&D activities to find out why there is a lack and depression of these activities in the industrial units. By considering the opportunity and challenges of these R&D units, there is a need to change these units to be active in order to quickly respond the market and demand requirements. Finally, a few alternative solutions and improvement plans are proposed, in which the Iranian R&D Society is responsible for supporting and succeeding these action plans towards the organization goals.R&D Management

Minimizing the total tardiness and makespan in an open shop scheduling problem with sequence-dependent setup times

We consider an open shop scheduling problem with setup and processing times separately such that not only the setup times are dependent on the machines, but also they are dependent on the sequence of jobs that should be processed on a machine. A novel bi-objective mathematical programming is designed in order to minimize the total tardiness and the makespan. Among several multi-objective decision making (MODM) methods, an interactive one, called the TH method is applied for solving small-sized instances optimally and obtaining Pareto-optimal solutions by the Lingo software. To achieve Pareto-optimal sets for medium to large-sized problems, an improved non-dominated sorting genetic algorithm II (NSGA-II) is presented that consists of a heuristic method for obtaining a good initial population. In addition, by using the design of experiments (DOE), the efficiency of the proposed improved NSGA-II is compared with the efficiency of a well-known multi-objective genetic algorithm, namely SPEA-II. Finally, the performance of the improved NSGA-II is examined in a comparison with the performance of the traditional NSGA-II

The effect of Salvia officinalis hydroalcoholic extract on PTZ-induced seizure threshold in Vincristine injected mice

and aims: Studies show that Vincristine is an anti-cancer drug which has neuropathic effects. Some studies have shown that Salvia officinalis has therapeutic effects on nervous system. The purpose of this study was to investigate the effects of Salvia officinalis hydroalcoholic extract and Vincristine on pentylenetetrazole (PTZ)-induced seizure threshould in mice. Methods: In this experimental study, 32 mice were randomly divided into 4 groups. The first group received normal saline, second group received Salvia officinalis hydroalcoholic extract (1 g/kg, i.p.), third group received Vincristine (10 µg/kg/day, i.v.) and finally the fourth group received hydroalcoholic extract of Salvia officinalis plus Vincristine. Then the seizure threshold was determined for each group after the injections. The data were analyzed using one way ANOVA followed by Tukey test. Results: The results of this study showed that hydroalcoholic extract of Salvia officinalis significantly increased the PTZ Induced seizure threshold (P<0.05). Simultaneous uses of Vincristine and Salvia officinalis extract caused a significant increase in seizure threshold in Vincristine group (P<0.05). Conclusion: Considering the existence of different types of ingredients in Salvia officinalis extract such as antioxidants, b-pinene and spathulenol, which have beneficial affects on the nervous system as well as their antioxidant effects, we can use this plant to reduce Vincristine induced neuropathic effects

An archived multi-objective simulated annealing for a dynamic cellular manufacturing system

To design a group layout of a cellular manufacturing system (CMS) in a dynamic environment, a multi-objective mixed-integer non-linear programming model is developed. The model integrates cell formation, group layout and production planning (PP) as three interrelated decisions involved in the design of a CMS. This paper provides an extensive coverage of important manufacturing features used in the design of CMSs and enhances the flexibility of an existing model in handling the fluctuations of part demands more economically by adding machine depot and PP decisions. Two conflicting objectives to be minimized are the total costs and the imbalance of workload among cells. As the considered objectives in this model are in conflict with each other, an archived multi-objective simulated annealing (AMOSA) algorithm is designed to find Pareto-optimal solutions. Matrix-based solution representation, a heuristic procedure generating an initial and feasible solution and efficient mutation operators are the advantages of the designed AMOSA. To demonstrate the efficiency of the proposed algorithm, the performance of AMOSA is compared with an exact algorithm (i.e., [-constraint method) solved by the GAMS software and a well-known evolutionary algorithm, namely NSGAII for some randomly generated problems based on some comparison metrics. The obtained results show that the designed AMOSA can obtain satisfactory solutions for the multi-objective model

A multi-objective model for designing a group layout of a dynamic cellular manufacturing system

This paper presents a multi-objective mixed-integer nonlinear programming model to design a group layout of a cellular manufacturing system in a dynamic environment, in which the number of cells to be formed is variable. Cell formation (CF) and group layout (GL) are concurrently made in a dynamic environment by the integrated model, which incorporates with an extensive coverage of important manufacturing features used in the design of CMSs. Additionally, there are some features that make the presented model different from the previous studies. These features include the following: (1) the variable number of cells, (2) the integrated CF and GL decisions in a dynamic environment by a multi-objective mathematical model, and (3) two conflicting objectives that minimize the total costs (i.e., costs of intra and inter-cell material handling, machine relocation, purchasing new machines, machine overhead, machine processing, and forming cells) and minimize the imbalance of workload among cells. Furthermore, the presented model considers some limitations, such as machine capability, machine capacity, part demands satisfaction, cell size, material flow conservation, and location assignment. Four numerical examples are solved by the GAMS software to illustrate the promising results obtained by the incorporated features

A three-stage assembly flow shop scheduling problem with blocking and sequence-dependent set up times

This paper considers a three-stage assembly flowshop scheduling problem with sequence-dependent setup times at the first stage and blocking times between each stage in such a way that the weighted mean completion time and makespan are minimized. Obtaining an optimal solution for this type of complex, large-sized problem in reasonable computational time using traditional approaches or optimization tools is extremely difficult. Thus, this paper proposes a meta-heuristic method based on simulated annealing (SA) in order to solve the given problem. Finally, the computational results are shown and compared in order to show the efficiency of our proposed SA

Solving an one-dimensional cutting stock problem by simulated annealing and tabu search

A cutting stock problem is one of the main and classical problems in operations research that is modeled as LP problem. Because of its NP-hard nature, finding an optimal solution in reasonable time is extremely difficult and at least non-economical. In this paper, two meta-heuristic algorithms, namely simulated annealing (SA) and tabu search (TS), are proposed and developed for this type of the complex and large-sized problem. To evaluate the efficiency of these proposed approaches, several problems are solved using SA and TS, and then the related results are compared. The results show that the proposed SA gives good results in terms of objective function values rather than TS