• Title/Summary/Keyword: Mathematical Programming

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Case Studies of Developing Creativity through Integrating Algorithmic Teaching into Mathematical Activities

  • Peng Aihui
    • Research in Mathematical Education
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    • v.9 no.4 s.24
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    • pp.341-350
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    • 2005
  • In this increasingly technological world, the creativity development has been highlighted much in many countries. In this paper, two mathematical activities with Chinese characteristics are presented to illustrate how to integrate algorithmic teaching into mathematical activities to develop students' creativity. Case studies show that the learning of algorithm can be transferred into creative learning when students construct their own algorithms in Logo environment rather than being indoctrinated the existing algorithms. Creativity development in different stages of mathematical activities and creativity development in programming are also discussed.

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Optimum Structural Design of Space truss with consideration in Snap-through buckling (뜀-좌굴을 고려한 공간 트러스의 최적구조설계에 관한 연구)

  • Shon, Su-Deok;Lee, Seung-Jae;Choi, Jae-Hyun
    • Journal of Korean Association for Spatial Structures
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    • v.12 no.2
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    • pp.89-98
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    • 2012
  • This study investigates the optimum structural design of space truss considering global buckling, and is to obtain the minimal weight of the structure. The mathematical programming method is used for optimization of each member by member force. Besides, dynamic programming method is adapted for consideration in snap-through buckling. The mathematical modeling for optimum design of truss members consists of objective function of total weight and constrain equations of allowable tensile (or compressive) stress and slenderness. The tangential stiffness matrix is examined to find the critical point on equilibrium path, and a ratio of the buckling load to design load is reflected in iteration procedures of dynamic programming method to adjust the stiffness of space truss. The star dome is examined to verify the proposed optimum design processor. The numerical results of the model are conversed well and satisfied all constrains. This processor is a relatively simple method to carry out optimum design with consideration in global buckling, and is viable in practice with respect to structural design.

Uncertain Centralized/Decentralized Production-Distribution Planning Problem in Multi-Product Supply Chains: Fuzzy Mathematical Optimization Approaches

  • Khalili-Damghani, Kaveh;Ghasemi, Peiman
    • Industrial Engineering and Management Systems
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    • v.15 no.2
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    • pp.156-172
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    • 2016
  • Complex and uncertain issues in supply chain result in integrated decision making processes in supply chains. So decentralized (distributed) decision making (DDM) approach is considered as a crucial stage in supply chain planning. In this paper, an uncertain DDM through coordination mechanism is addressed for a multi-product supply chain planning problem. The main concern of this study is comparison of DDM approach with centralized decision making (CDM) approach while some parameters of decision making are assumed to be uncertain. The uncertain DDM problem is modeled through fuzzy mathematical programming in which products' demands are assumed to be uncertain and modeled using fuzzy sets. Moreover, a CDM approach is customized and developed in presence of fuzzy parameters. Both approaches are solved using three fuzzy mathematical optimization methods. Hence, the contribution of this paper can be summarized as follows: 1) proposing a DDM approach for a multi-product supply chain planning problem; 2) Introducing a coordination mechanism in the proposed DDM approach in order to utilize the benefits of a CDM approach while using DDM approach; 3) Modeling the aforementioned problem through fuzzy mathematical programming; 4) Comparing the performance of proposed DDM and a customized uncertain CDM approach on multi-product supply chain planning; 5) Applying three fuzzy mathematical optimization methods in order to address and compare the performance of both DDM and CDM approaches. The results of these fuzzy optimization methods are compared. Computational results illustrate that the proposed DDM approach closely approximates the optimal solutions generated by the CDM approach while the manufacturer's and retailers' decisions are optimized through a coordination mechanism making lasting relationship.

A State Space Modeling and Evolutionary Programming Approach to Automatic Synthesis of Chemical Processes

  • Choi, Soo-Hyoung;Lee, Bom-Sock;Chung, Chang-Bock
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.1870-1873
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    • 2004
  • The objective of this study is to investigate the possibility of chemical process synthesis purely based on mathematical programming when given an objective, feed conditions, product specifications, and model equations for available process units. A method based on a state space approach is proposed, and applied to an example problem with a reactor, a heat exchanger, and a separator. The results indicate that a computer can automatically synthesize an optimal process without any heuristics or expertise in process design provided that global optimization techniques are improved to be suitable for large problems.

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The Role of S-Shape Mapping Functions in the SIMP Approach for Topology Optimization

  • Yoon, Gil-Ho;Kim, Yoon-Young
    • Journal of Mechanical Science and Technology
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    • v.17 no.10
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    • pp.1496-1506
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    • 2003
  • The SIMP (solid isotropic material with penalization) approach is perhaps the most popular density variable relaxation method in topology optimization. This method has been very successful in many applications, but the optimization solution convergence can be improved when new variables, not the direct density variables, are used as the design variables. In this work, we newly propose S-shape functions mapping the original density variables nonlinearly to new design variables. The main role of S-shape function is to push intermediate densities to either lower or upper bounds. In particular, this method works well with nonlinear mathematical programming methods. A method of feasible directions is chosen as a nonlinear mathematical programming method in order to show the effects of the S-shape scaling function on the solution convergence.

A Mathematical Programming Approach for Block Storage Problem in Shipbuilding Process (수리 모형을 이용한 조선 산업에서의 블록 적치장 최적 운영 계획 도출)

  • Ha, Byung-Hyun;Son, Jung-Ryoul;Cho, Kyu Kab;Choi, Byung-Cheon
    • Korean Management Science Review
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    • v.30 no.3
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    • pp.99-111
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    • 2013
  • This paper studies the scheduling problem of storing and retrieving assembly blocks in a temporary storage yard. The objective is to minimize the number of relocations of blocks while the constraints for storage and retrieval time windows are satisfied. We present an integer programming model based on multi-commodity network flows, and the three revised models based on the properties of the problem. We show that the revised models are more efficient than the generic model through the numerical experiments.

Design and Implementation of Mathematical Programming Software-LinPro (數理計劃 소프트웨어 LinPro의 설계 및 구현)

  • 양광민
    • Journal of the Korean Operations Research and Management Science Society
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    • v.12 no.1
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    • pp.139-139
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    • 1987
  • This study addresses basic requirements for mathematical programming software, discusses considerations in designing these software, implementation issues facing in these types of applications development, and shows some examples of codes being developed in the course. This type of projects requires long and ever-changing evolutionary phases. The experience is therefore, valuaable in suggesting some useful hints which may be salvaged for similar projects as well as providing reusable codes. In particular, scanning and parsing the free-format inputs, symbol table management, mixed-language programming, and data structures dealing with large sparse matrices are indispensable to many management science software development. Extensions to be made are also discussed.

Nonlinear programming approach for a class of inverse problems in elastoplasticity

  • Ferris, M.C.;Tin-Loi, F.
    • Structural Engineering and Mechanics
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    • v.6 no.8
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    • pp.857-870
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    • 1998
  • This paper deals with a special class of inverse problems in discrete structural plasticity involving the identification of elastic limits and hardening moduli on the basis of information on displacements. The governing equations lead naturally to a special and challenging optimization problem known as a Mathematical Program with Equilibrium Constraints (MPEC), a key feature of which is the orthogonality of two sign-constrained vectors or so-called "complementarity" condition. We investigate numerically the application of two simple algorithms, both based on the use of the general purpose nonlinear programming code CONOPT accessed via the GAMS modeling language, for solving the suitably reformulated problem. Application is illustrated by means of two numerical examples.

SECOND-ORDER UNIVEX FUNCTIONS AND GENERALIZED DUALITY MODELS FOR MULTIOBJECTIVE PROGRAMMING PROBLEMS CONTAINING ARBITRARY NORMS

  • Zalmai, G.J.
    • Journal of the Korean Mathematical Society
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    • v.50 no.4
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    • pp.727-753
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    • 2013
  • In this paper, we introduce three new broad classes of second-order generalized convex functions, namely, ($\mathcal{F}$, $b$, ${\phi}$, ${\rho}$, ${\theta}$)-sounivex functions, ($\mathcal{F}$, $b$, ${\phi}$, ${\rho}$, ${\theta}$)-pseudosounivex functions, and ($\mathcal{F}$, $b$, ${\phi}$, ${\rho}$, ${\theta}$)-quasisounivex functions; formulate eight general second-order duality models; and prove appropriate duality theorems under various generalized ($\mathcal{F}$, $b$, ${\phi}$, ${\rho}$, ${\theta}$)-sounivexity assumptions for a multiobjective programming problem containing arbitrary norms.