Inverse optimisation and linear programming have emerged as crucial instruments in addressing complex decision-making problems where underlying models must be inferred from observed behaviour. At its ...

DUBLIN--(BUSINESS WIRE)--Research and Markets(http://www.researchandmarkets.com/research/799091/deterministic_oper) has announced the addition of John Wiley and Sons ...

Journal of Computational Mathematics, Vol. 31, No. 4 (July 2013), pp. 335-354 (20 pages) In this paper, we consider the solution of the standard linear programming (LP). A remarkable result in LP ...

Integer programming is a crucial branch of mathematical optimisation that focuses on problems where some or all decision variables are constrained to be integers. This field underpins many practical ...

This paper presents a novel approach to the joint optimization of job scheduling and data allocation in grid computing environments. We formulate this joint optimization problem as a mixed integer ...

Note that the optimal solution to Gonzaga’s problem denoted by (G) is [a, 0] T with an optimal value of the objective function equal to a, a ≥ 10. From the infeasible starting point e = [1, 1] T, the ...

To fulfill the 2 Core Courses, take two Core Courses from two different Core Areas. CSE Core Courses are classified into six areas: Introduction to CSE, Computational Mathematics, High Performance ...

Estimation errors or uncertainities in expected return and risk measures create difficulties for portfolio optimization. The literature deals with the uncertainty using stochastic, fuzzy or ...

This program is offered by the Department of Management Science and Information Systems (MSIS). It is the continuation of the previous concentration in Management Science and the program of Operations ...

Linear programming is a mathematical optimization technique used to optimize a linear objective function subject to a set of linear constraints. It involves finding the values of decision variables ...