Algorithm and software for the optimal technological design of a system of simple distillation columns

Objectives. The formalized problem of the optimal design of distillation column systems belongs to the class of mixed integer nonlinear program problems. Discrete search variables are the number of trays in the rectifying and stripping sections of columns, whereas the continuous ones are the operating modes of columns. This study aimed to develop an algorithm and a software package for the optimal technological design of a system of simple distillation columns based on the criterion of total reduced capital and energy costs using rigorous mathematical distillation models.Methods. The solution to this problem is based on the branch and bound method. A computer model of the distillation column system was developed in the environment of the Aspen Hysys software package. The Inside–Out module was used as the distillation model. The developed algorithm is implemented in the software environment of the Matlab mathematical package. To solve the conditional optimization problem, a sequential quadratic programming method-based model was used. The interaction between software add-ins in Matlab and Aspen Hysys is implemented using a Component Object Model interface.Results. Approaches to obtain the lower and upper bounds of the optimality criterion and the branching method for the implementation of the branch and bound method have been developed. In addition, an algorithm for the optimal design of a distillation column of a given topology based on the branch and bound method has been developed. Furthermore, using Matlab, a software package that implements the developed algorithm and is integrated with the universal modeling software AspenHysys has been created.Conclusions. An algorithm and a software package have been developed and implemented that allows automating the design process of distillation column systems and integration with advanced mathematical programming packages, respectively. The performance of the algorithm and software package has been evaluated using the optimal design of the debutanization column as an example.

Comparison of various algorithms based on TSP solving

The traveling salesman problem (TSP) is a classic combinatorial optimization problem. As a hot research problem, it has been applied in many fields. Since there is currently no algorithm with good performance that can perfectly solve this problem, for the solution of the traveling salesman problem, this article first establishes a mathematical model of the traveling salesman problem, and uses four solving methods for the same case: the greedy method, Branch and bound method, dynamic programming method and genetic algorithm, analyze the applicability and accuracy of different algorithms in the same case.

Maksimasi Keuntungan Layanan Jasa Be Clean Laundry Dengan Menerapkan Metode Branch And Bound

The purpose of this research is to find the maximize benefits from Be Clean Laundry business. In optimize laundry business by looking at the limited resources of the business used branch and bound method. Using the branch and bound method assisted by QM software in more optimal laundry, coat 53 kg, doll 32 kg, blanket 95 kg, bedcover 105 kg, gordyn 91 kg, and clothes 805 kg with a profit of Rp. 4.027.000, while the previous profit based on estimate made by the laundry Owner of Rp. 4.000.000 increase of 0,7 %.

Quantity decisions of two-stage competitive location model based on different location modes

The facility location of a competing firm in a market has great importance in supply chain management. The two-stage competitive location model formulates the decision process of an entrant firm facing both location and price competition. In this paper, we incorporated the facility quantity as a decision variable into a two-stage competitive location model with the objective of maximized profit. Sequential location mode and simultaneous location mode were applied to simulate different location behavior. We developed an approximate branch and bound method to accelerate optimal location searching speed under the premise of accuracy. Greedy algorithm and approximate branch and bound method were used in two location modes. From algorithm evaluation, we found that the approximate branch and bound method is an ideal supplement of the traditional branch and bound method, especially for location problems with large-scale potential locations. Compare the results of the two modes, we found when a new firm is going to enter a market with both price and location competition, sequential location mode is an advantage strategy, since it can gain more profit than simultaneous location mode.