tailieunhanh - Ebook Mathematics for economics and business (8th edition): Part 2

(BQ) Part 2 book "Mathematics for economics and business" has contents: Partial differentiation, integration, matrices, linear programming, dynamics, answers to problems. | CHAPTER 5 Partial Differentiation This chapter continues the topic of calculus by describing how to differentiate functions of more than one variable. In many ways this chapter can be regarded as the climax of the whole book. It is the summit of the mathematical mountain that we have been merrily climbing. Not only are the associated mathematical ideas and techniques quite sophisticated, but also partial differentiation provides a rich source of applications. In one sense there is no new material presented here. If you know how to differentiate a function of one variable then you also know how to partially differentiate a function of several variables because the rules are the same. Similarly, if you can optimise a function of one variable then you need have no fear of unconstrained and constrained optimisation. Of course, if you cannot use the elementary rules of differentiation or cannot find the maximum and minimum values of a function as described in Chapter 4 then you really are fighting a lost cause. Under these circumstances you are best advised to omit this chapter entirely. There is no harm in doing this, because it does not form the prerequisite for any of the later topics. However, you will miss out on one of the most elegant and useful branches of mathematics. There are six sections. It is important that Sections and are read first, but the remaining sections can be studied in any order. Sections and follow the familiar pattern. We begin by looking at the mathematical techniques and then use them to determine marginal functions and elasticities. Section describes the multiplier concept and completes the topic of national income determination which you studied in Chapter 1. The final three sections are devoted to optimisation. For functions of several variables, optimisation problems are split into two groups, unconstrained and constrained. Unconstrained problems, tackled in Section , involve the .

• Quản trị kinh doanh
• Mathematics for economics
• Mathematics for business
• Partial differentiation
• Linear programming
• Differential equations
• Linear programming problems
• Multi objective bi level linear programming problems
• Partial information of preference
• Fuzzy environment
• Parametric linear programming problems
• Parametric space
• Ebook Linear optimization
• Linear optimization
• Linear extensions
• The linear programming problem
• Simplex algorithms
• Primal dual pairs
• Fuzzy linear programming
• Fuzzy number
• Modified subgradient method
• Fuzzy decisive set method
• Fuzzy technological coefficients
• Simplex type algorithms
• Primal dual exterior point algorithm
• Computational study
• Linear Programming Problem
• Triangular fuzzy number
• Trapezoidal fuzzy number
• Multi choice programming
• Fuzzy programming
• Data envelopment analysis (DEA)
• Multiple objective linear programming (MOLP)
• MOLP formulation
• Measuring relative efficiency
• Journal of Computer Science and Cybernetics
• Alternating current electrical systems
• Integer quadratic programming
• Non linear knapsack problems arising
• Polynomial time approximation schemes
• Optimal decision
• Economic order quantity
• Fuzzy Non Linear Programming Technique
• Real inventory problems
• Probabilistic models
• Interval linear programming
• Robust two step method
• Three step method
• Optimality condition
• Robust TSM
• Two phase linear programming
• Redundancy allocation
• Redundant components
• System reliability
• BMC Bioinformatics
• Chromosome structure
• Chromosomal rearrangement
• Ancestral genome
• Transformation of chromosome structures
• Parsimony principle
• Integer linear programming
• Management science linear programming
• Computer solution
• Assignment problems
• Modeling examples
• Integer programming
• Network flow models
• Dynamic programming
• NP complete problems
• Coping with NP completeness
• Quantum algorithms
• Intelligent exhaustive search
• Management science
• Network optimization problems
• Binary integer programming
• Basic concepts
• Newton’s method
• Goodman’s method
• Projected Hessian
• Interior point
• Nonlinear programming
• Numerical comparisons
• Quadratic forms
• Semidefinite matrices
• Lagrangian duality
• Non linear programming
• Positive semidefinite
• Genetic Algorithm
• Optimal Recombination Problem
• Boolean Linear Programming
• Optimal recombination
• Design and Analysis of Algorithms
• Analysis of Algorithms
• Design of Algorithms
• Data structures