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transportation problem-solutionsolution of the transportation problemthe fundamental steps of the transportation method arestep 1
transportation model tablea more compact method for representing the transportation model than the linear equations is to use what we call the
application of transportation modelin the direct logic the transportation model looks for the determination of a transportation plan of a particular
transportation modelin the obvious sense the model deals with the determination of a minimum cost plan for transporting a single commodity from a
use of computer systems in linear programmingwhen a computer is to be used for linear programming there are a number of steps1 development of the
advantages and limitations of dynamic programmingadvantages1 in certain types of problems such as inventory control management chemical engineering
dynamic programmingit is an extension which finds solutions to problems involving a number of decisions which have to be made sequentially for
integer programmingit is a technique for solving a linear programming model with an added constraint that the decision variables must only be
extensions to linear programmingin many real situations the solutions to linear programming models make sense only if they have integer values
maximum change in marginal profit or costjust as we did in studying the permissible ranges for changes in resources we are also interested in
status resourceswe had classified constraints as scarce and abundant depending respectively on whether or not the optimum solution consumes the
optimum solutionfrom the stand point of implementing the lp solution the mathematical classification of the variables as basic and non-basic is of no
adjacent extreme points differ in only one variablethe first observation indicates that we can identify the extreme points of the solution space
the simplex methodin the graphical solution the optimum solution is always associated with a corner or extreme point of the solution space the
objective functionalthough the standard lp model can be either the maximization or the minimization type it is sometimes useful to convert one form
variablesunrestricted variable yi can be expressed in terms of two non-negative variables by using the substitutionyi yi - yi yi yi ge 0the
constraints1 a constraint of the type le ge can be converted to an equation by adding a slack variable to subtracting a surplus variable form the
linear programming this section introduces the general method called the simplex algorithm which is designed to solve any linear program
disadvantages of simulation1 although all models are simplification of reality they may still be complex and require a substantial amount of
advantages of simulation1 it can be used in areas where analytical techniques are not available or would be too complex2 constructing the model
the role of computers in simulationcomputers can be used to1 to generate the random numbers2 to simulate thousands of trials this is done extremely
constructing the modelsteps1 identify the objectives of the simulation a detailed listing of the results expected will help to clarify the output
types of non-controlled variablesa parametersthese are input variables that for a given simulation have a constant value they are factors which help
input or exogenous variablesthese are variables of two types1 controlled variables these are variables that can be controlled by management by
types of simulation1 operational gaining methodthis refers to those situations involving conflict of interest among players or decision makers within