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    An Effective Heuristic Method to Minimize Makespan and Flow Time in a Flow Shop Problem
    (Science and Information Organization, 2020-01-01)
    In this paper, it is presented a heuristic method for solving the multi-objective flow shop problem. The work carried out considers the simultaneous optimization of the makespan and the flow time; both objectives are essential in measuring the production system's performance since they aim to reduce the completion time of jobs, increase the efficiency of resources, and reduce waiting time in queue. The proposed method is an adaptation of multi-objective Newton's method, which is applied to problems with functions of continuous variables. In this adaptation, the method seeks to improve a sequence of jobs through local searches recursively. The computational experiments show the potential of the proposed method to solve medium-sized and large instances compared with other existing literature methods.
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    Application of piecewise linear approximation method for the estimation of origin-destination matrix
    (Science and Information Organization, 2020-01-01)
    This paper presents a Mixed-Integer Programming Model for the urban freight transport planning problem through the estimation of the Origin-Destination Matrix. The Origin-Destination Matrix is used to know the pattern of travel or vehicle flow between different zones of a city and is estimated from the counting of vehicles on the routes of a road network. For the estimation of the Origin-Destination Matrix, the Entropy Maximization approach is applied. This approach is based on a non-linear optimization model. In order to overcome this difficulty, an optimization model based on the Piecewise Linear Approximation Method is proposed. To test the proposed model, an instance was built based on a road network of a real case. The proposed model obtained good results in a reduced computational time, demonstrating its usefulness for the urban freight transport planning.