International Journal of Industrial Engineering & Production Research

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In this paper, we consider scheduling of project networks under minimization of total weighted resource tardiness penalty costs. In this problem, we assume constrained resources are renewable and limited to very costly machines and tools which are also used in other projects and are not accessible in all periods of time of a project. In other words, there is a dictated ready date as well as a due date for each resource such that no resource can be available before its ready date but the resources are allowed to be used after their due dates by paying penalty cost depending on the resource type. We also assume, there is only one unit of each resource type available and no activity needs more than it for execution. The goal is to find a schedule with minimal total weighted resource tardiness penalty costs. For this purpose, we present a hybrid metaheuristic procedure based on the greedy randomized adaptive search algorithm and path-relinking algorithm. We develop reactive and non-reactive versions of the algorithm. Also, we use different bias probability functions to make our solution procedure more efficient. The computational experiments show the reactive version of the algorithm outperforms the non-reactive version. Moreover, the bias probability functions defined based on the duration and precedence relation characteristics give better results than other bias probability functions.

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Network location models comprise one of the main categories of location models. These models have various applications in regional and urban planning as well as in transportation, distribution, and energy management. In a network location problem, nodes represent demand points and candidate locations to locate the facilities. If the links network is unchangeably determined, the problem will be an FLP (Facility Location Problem). However, if links can be added to the network at a reasonable cost, the problem will then be a combination of facility location and NDP (Network Design Problem) hence, called FLNDP (Facility Location Network Design Problem), a more general variant of FLP. In previous studies of this problem, capacity of facilities was considered to be a constraint while capacity of links was not considered at all. The proposed MIP model considers capacity of facilities and links as decision variables. This approach increases the utilization of facilities and links, and prevents the construction of links and location of facilities with low utilization. Furthermore, facility location cost (link construction cost) in the proposed model is supposed to be a function of the associated facility (link) capacity. Computational experiments as well as sensitivity analyses performed indicate the efficiency of the model.

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In this paper, a multivariable control of a two-link robot is performed by fuzzy-sliding mode control. Robots on the one hand have complex dynamics due to nonlinearity, uncertainty and indeterminacy resulting from friction and other factors. The uncertainty and nonlinearity of the governing equations more and more necessitates the use of these two types of controllers in spite of a two-link and multivariable dynamic system. In this paper simulation, a fuzzy system is used in two parts. In the first part, a fuzzy system is used to approximate the uncertainty of the robot arm dynamic model in the control law and in the second part the nonlinear term of the signal function is replaced by an adaptive neuro-fuzzy controller to produce appropriate s and to track the output properly. The comparison of simulation results suggests that the intelligent method based on the proposed adaptive neuro-fuzzy control has better performance in tracking reference signal with slight tracking error and higher accuracy compared to sliding mode method.