## Introduction to Operations ResearchCD-ROM contains: Student version of MPL Modeling System and its solver CPLEX -- MPL tutorial -- Examples from the text modeled in MPL -- Examples from the text modeled in LINGO/LINDO -- Tutorial software -- Excel add-ins: TreePlan, SensIt, RiskSim, and Premium Solver -- Excel spreadsheet formulations and templates. |

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Page 382

The objective is to determine how all n

the total cost . Any problem satisfying all these assumptions can be solved

extremely efficiently by algorithms designed specifically for

.

The objective is to determine how all n

**assignments**should be made to minimizethe total cost . Any problem satisfying all these assumptions can be solved

extremely efficiently by algorithms designed specifically for

**assignment**problems.

Page 399

Consider the

management has decided that each new product should be

plant and that no plant should be

Consider the

**assignment**problem having the following cost table . ... Therefore ,management has decided that each new product should be

**assigned**to only oneplant and that no plant should be

**assigned**more than one product ( so that ...Page 400

( c ) Reformulate this

problem with two sources and three ... ( c ) . choice of these

to distribution centers is to be made solely on the basis of minimizing total

shipping cost .

( c ) Reformulate this

**assignment**problem as an equivalent transportationproblem with two sources and three ... ( c ) . choice of these

**assignments**of plantsto distribution centers is to be made solely on the basis of minimizing total

shipping cost .

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### Common terms and phrases

activity additional algorithm allocation allowable amount apply assignment basic solution basic variable BF solution bound boundary called changes coefficients column complete Consider constraint Construct corresponding cost CPF solution decision variables demand described determine distribution dual problem entering equal equations estimates example feasible feasible region feasible solutions FIGURE final flow formulation functional constraints given gives goal identify illustrate increase indicates initial iteration linear programming Maximize million Minimize month needed node nonbasic variables objective function obtained operations optimal optimal solution original parameters path plant possible presented primal problem Prob procedure profit programming problem provides range remaining resource respective resulting revised shown shows side simplex method simplex tableau slack solve step supply Table tableau tion unit values weeks Wyndor Glass zero