Advanced Operation Research Techniques

(a)                  Non-linear programming is that form of programming in which some or all of the variables are curvilinear. In other words this means that either the objective function or constraints or both are not in linear form. In most of the practical situations. We encounter with non-linear programming problems but for computational purposes we approximate them as linear programming problems. Even then there may be some non-linear programming problem which may not be fully solved but presently known methods.

(b)                  Dynamic programming refers to a systematic search for optimal solutions to problems that involve May highly complex interrelations that are moreover sensitive to multistage effects such as successive time phases. Dynamic problems involve manipulation of a large amount of information and require electronic computers.

(c)                   Integer programming. Integer programming applies when the values of decision variables are restricted to integers. Applications include financial management and plant location.

(d)                  Goal programming. Goal programming deals with problems having multiple objectives. It is a technique quite similar to linear programming. Applications include production scheduling, transportation problems portfolio analysis and crop selection in agriculture.

(e)                   Heuristics programming. Also known as discovery method refers to step by step search toward an optimal when a problem cannot be expressed in mathematical programming form. The search procedure examines successively a series of combinations that lead to stepwise improvement in the solution and the search stops when a near optimal has been found.

(f)                   Algorithmic programming. Is just the opposite of Heurisitic programming. It may also be termed as mathematical programming. This programming refers to a thorough and exhaustive mathematical approach to investigate all aspects of the given variables in order to obtain optimal solution.

(g)                  Quadratic programming refers to a modification of linear programming, in which the objective function and constraint equations appear in quadratic form, i.e., they contain terms.

(h)                  Parametric programming is the name given to linear programming when the latter is modified for the purpose of inclusion of several objective equations with varying degrees of priority. The sensitivity of the solution to these variations then studied.

(i)                    Probabilistic programming also known as stochastic programming refers to linear programming that includes an evaluation of relative risks and uncertainties in various alternatives of choice for management decisions.

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