Mathematical Programming Algorithms Help

Mathematical Programming: Theory and Algorithms Basic Population Analysis

he branch of mathematics concerned with the theory and methods for solving problems on finding the extremes of functions on sets defined by linear and non-linear constraints (equalities and inequalities) in a finite-dimensional vector space. Mathematical programming is a branch of operations research, which comprises a wide class of control problems the mathematical models of which are finite-dimensional extremum problems. The problems of mathematical programming find applications in various areas of human activity where it is necessary to choose one of the possible ways of action, e.g. in solving numerous problems of control and planning of production processes as well as in problems of design and long-term planning. The term “mathematical programming” is connected with the fact that the goal of solving various problems is choosing programs of action

Applications of Linear Programming, Integer Programming, and Non-linear Programming have not been restricted to the area of Operations and Economics. Nowadays, they have become pivotal factors in the area of Statistics with regards to Mathematical Programming.  Though these concepts are basic and lay the foundation of students in the world of mathematical programming, they can be complex at times. Our talented pool of Statistics experts, Statistics assignment tutors and Statistics homework tutors can cater to your entire needs in the area of Mathematical Programming such as Assignment Help, Homework Help, Project Paper Help and Exam Preparation Help.

Following is the list of comprehensive topics in which we offer the quality solutions

  • Mathematical foundations of mathematical programming
  • Integer linear programming (ILP) methods (branch and bound, enumeration, cutting planes)
  • Decomposition methods
  • Probability
  • Quantitative Methods
  • Math Statistics Questions
  • Theory and the solution of linear and nonlinear programming problems
  • Simplex and interior point algorithms
  • Quadratic programming