This paper presents an efficient and compact Matlab code to solve three-dimensional topology optimization problems. The 169 lines comprising this code include finite element analysis, sensitivity analysis, density fil...
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This paper presents an efficient and compact Matlab code to solve three-dimensional topology optimization problems. The 169 lines comprising this code include finite element analysis, sensitivity analysis, density filter, optimality criterion optimizer, and display of results. The basic code solves minimum compliance problems. A systematic approach is presented to easily modify the definition of supports and external loads. The paper also includes instructions to define multiple load cases, active and passive elements, continuation strategy, synthesis of compliant mechanisms, and heat conduction problems, as well as the theoretical and numerical elements to implement general non-linear programming strategies such as SQP and MMA. The code is intended for students and newcomers in the topology optimization. The complete code is provided in Appendix C and it can be downloaded from http://***.
nonlinear clearing functions, an idea initially suggested to reflect congestion effects in production planning, are used to express throughput of facilities prone to congestion in a facility location problem where eac...
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nonlinear clearing functions, an idea initially suggested to reflect congestion effects in production planning, are used to express throughput of facilities prone to congestion in a facility location problem where each demand site is served by exactly one facility. The traditional constant capacity constraint for a facility is replaced with the nonlinear clearing function. The resulting nonlinear integer problem is solved by a column generation heuristic in which initial columns for the restricted master problem are generated by known existing algorithms and additional columns by a previously developed dynamic programming algorithm. Computational experimentation in terms of dual gap and CPU time based on both randomly generated and published data sets show not only clear dominance of the column generation over a Lagrangian heuristic previously developed, but also the high quality of results from the suggested heuristic for large problems.
This paper presents a non-linear programming model for online balancing of the work-in-queue (WIQ) of a fast response production system that consists of multiple workstations and diverse part mix. The model resembles ...
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This paper presents a non-linear programming model for online balancing of the work-in-queue (WIQ) of a fast response production system that consists of multiple workstations and diverse part mix. The model resembles a multiple product CONWIP system with a variety of products' routings and bottlenecks. It maximises a global benefit of the production system subject to delay and loading rate bounds. The upper bounds on the delay symbolise the desired level of WIQ. The approach relies on the delay of the authorisation cards as a measure of the actual system WIQ. A real-time primal-dual algorithm associated with each part type is used to solve the optimisation problem in a decentralised manner. The algorithm solves for the optimal rates in a timely decentralised iterative way without the access to the global information of the production system. Each part route calculates its loading rate according to the arrival of the authorisation cards. Extensive simulation experiments were conducted to demonstrate the reliability of the algorithm. The calculated rates were found to be proportional to the level of WIQ at each workstation with reasonable resource allocation achieved between the different routes.
This paper demonstrates a new approach to yield all potential equilibria in a system with multiple actors by computing the Grobner basis of the original problem. Further, it discusses the advantages of choosing this m...
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This paper demonstrates a new approach to yield all potential equilibria in a system with multiple actors by computing the Grobner basis of the original problem. Further, it discusses the advantages of choosing this method over traditional numerical approaches. In addition, it provides a concept that applies machine learning, specifically evolution strategies, to approximate utility functions. This is done in order to remove the requirement for solving the dual problem of the system and thus allows to scale the equilibrium computation method to larger, more complex problem setups. This is demonstrated by a novel case study on non-convex players in form of hydropower generators operating simultaneously on spot and reserve markets whilst considering startups and shutdowns, periodical inflows and non-linear water conversion head effects. The model is further extended by considering uncertainty under unknown distributions and solved for a large-scale example in form of a multi-area network resembling the Scandinavian power system. (C) 2020 Elsevier B.V. All rights reserved.
Recent information and communication developments caused that global organizations spread out their markets throughout the world. In this environment, local exclusive markets have been replaced with global competitive...
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Recent information and communication developments caused that global organizations spread out their markets throughout the world. In this environment, local exclusive markets have been replaced with global competitive ones. Therefore, organizations must concentrate on their main operations to survive in such an environment. To do so, managers have intended to cooperate with some financial partners in long-term relations. In this paper, the aim is to develop a fuzzy analytic network process (ANP) model to evaluate the potential suppliers and select the best one(s) with respect to the vendor important factors. Additionally, ANP is developed by fuzzy sets theory to cover the indeterminacy of decisions made in this field. The authors have augmented the model with a non-linear programming model to elicit eigenvectors from fuzzy comparison matrices. Hybridization of these two concepts can model supplier selection problem in all circumstances and reaches the optimal choice. Finally, a numerical sample is used to validate the proposed model. (C) 2009 Elsevier Ltd. All rights reserved.
A methodology based on genetic algorithm has been developed for lower cost design of new, and augmentation of existing water distribution networks. The results have been compared with those of non-linear programming t...
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A methodology based on genetic algorithm has been developed for lower cost design of new, and augmentation of existing water distribution networks. The results have been compared with those of non-linear programming technique through application to several case studies. The genetic algorithm results in a lower cost solution. Parameters governing the convergence of the solutions in non-linear and genetic algorithms are also discussed. (C) 1999 Elsevier Science Ltd. All rights reserved.
During the last decade various methods have been proposed to handle linear and non-linear constraints by using genetic algorithms to solve problems of numerical optimization. The key to success lies in focusing the se...
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During the last decade various methods have been proposed to handle linear and non-linear constraints by using genetic algorithms to solve problems of numerical optimization. The key to success lies in focusing the search space towards a feasible region where a global optimum is located. This study investigates an approach that adaptively shifts and shrinks the size of the search space to the feasible region it uses two strategies for estimating a point of attraction. Several test cases demonstrate the ability of this approach to reach effectively and accurately the global optimum with a low resolution of the binary representation scheme and without additional computational efforts. Copyright (C) 2004 John Wiley Sons, Ltd.
The design or composite beams is complicated and highly iterative. Depending on the design parameters a beam can be fully composite or partially composite. In the case of design on the basis of the American Institute ...
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The design or composite beams is complicated and highly iterative. Depending on the design parameters a beam can be fully composite or partially composite. In the case of design on the basis of the American Institute of Steel Construction (AISC) Load and Resistance Factor Design (LRFD) one has to consider the plastic deformations. As pointed out by Lorenz, the real advantage of the LRFD code can be realized in the minimum cost design. In this article, we present a general formulation for the cost optimization of composite beams based on the AISC LRFD specifications by including the costs of (a) concrete, (b) steel beam, and (c) shear studs. The problem is formulated as a mixed integer-discrete nonlinearprogramming problem and solved by the recently patented neural dynamics model of Adeli and Park (U.S. patent 5,815,394 issued on September 29, 1998). It is shown that use of the cost optimization algorithm presented in this article results in substantial cost savings. Copyright (C) 2001 John Wiley & Sons, Ltd.
This paper extended the concept of the technique for order preference by similarity to ideal solution (TOPSIS) to develop a methodology for solving multi-level non-linear multi-objective decision-making (MLN-MODM) pro...
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This paper extended the concept of the technique for order preference by similarity to ideal solution (TOPSIS) to develop a methodology for solving multi-level non-linear multi-objective decision-making (MLN-MODM) problems of maximization-type. Also, two new interactive algorithms are presented for the proposed TOPSIS approach for solving these types of mathematical programming problems. The first proposed interactive TOPSIS algorithm includes the membership functions of the decision variables for each level except the lower level of the multi-level problem. These satisfactory decisions are evaluated separately by solving the corresponding single-level MODM problems. The second proposed interactive TOPSIS algorithm lexicographically solves the MODM problems of the MLN-MOLP problem by taking into consideration the decisions of the MODM problems for the upper levels. To demonstrate the proposed algorithms, a numerical example is solved and compared the solutions of proposed algorithms with the solution of the interactive algorithm of Osman et al. (2003)141. Also, an example of an application is presented to clarify the applicability of the proposed TOPSIS algorithms in solving real world multi-level multi-objective decision-making problems. (C) 2013 Elsevier Inc. All rights reserved.
An important concept proposed in the early stage of robot path planning field is the shrinking of the robot to a point and meanwhile expanding of the obstacles in the workspace as a set of new obstacles. The resulting...
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An important concept proposed in the early stage of robot path planning field is the shrinking of the robot to a point and meanwhile expanding of the obstacles in the workspace as a set of new obstacles. The resulting grown obstacles are called the Configuration Space (Cspace) obstacles. The find-path problem is then transformed into that of finding a collision free path for a point robot among the Cspace obstacles. However. the research experiences obtained so far have shown that the calculation of the Cspace obstacles is very hard work when the following Situations occur: 1. both the robot and obstacles are not polygons and 2. the robot is allowed to rotate. This situation is even worse when the robot and obstacles are three dimensional (3D) objects with various shapes. Obviously a direct path planning approach without the calculation of the Cspace obstacles is strongly needed. This paper presents Such a new real-time robot path planning approach which. to the best Of our knowledge, is the first one in the robotic community. The fundamental ideas are the utilization of inequality and optimization technique. Simulation results have been presented to show its merits.
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