Mathematical Programming: Optimization Models for Business and Management Decision-makingThis text focuses on a particular group of management science models, known collectively as mathematical programming, and the potential application of such models to business problems and decision-making. |
Contents
Part A Transportation and assignment | 15 |
Extensions to the transportation model | 43 |
Part B Linear programming | 70 |
Copyright | |
11 other sections not shown
Common terms and phrases
algorithm allocation apply approach appropriate artificial variable assembly hours assignment basic variables beignets binding constraints branch and bound business problem calculations chapter column cost coefficient current solution decision problems decision variables decision-maker Depot B Depot Depot D Origin derivative Destination requirement 200 determine DIEGO dual effect empty cell equations examine example factory feasible area feasible solution given goal Goal Programming IMC's improvement index increase indicates infeasible integer introduced knapsack problem Lagrange multiplier linear programming mathematical programming models Maximize maximum microchips minimization problem MODI method monitors non-basic variables non-linear objective function opportunity cost optimum original problem primal problem formulation production profit quantity represents S₁ S₂ sensitivity analysis shown in Table Simplex algorithm Simplex method slack variables solution method solve stage stepping stone method Student activity supply surplus variable tableau Team technique total cost Transportation table whilst X₁ zero