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Page 192
This situation is summarized in Table 5.1, where defining equations refer to the
constraint boundary equations that yield (define) the indicated CPF solution. For
any linear programming problem with n decision variables, each CPF solution
lies ...
This situation is summarized in Table 5.1, where defining equations refer to the
constraint boundary equations that yield (define) the indicated CPF solution. For
any linear programming problem with n decision variables, each CPF solution
lies ...
Page 199
Recall that each comer-point solution is the simultaneous solution of a system of
n constraint boundary equations, which we called its defining equations. The key
question is: How do we tell whether a particular constraint boundary equation is ...
Recall that each comer-point solution is the simultaneous solution of a system of
n constraint boundary equations, which we called its defining equations. The key
question is: How do we tell whether a particular constraint boundary equation is ...
Page 222
(b) Develop a table giving each of the CPF solutions and the corresponding
defining equations, BF solution. and nonbasic variables. Calculate Z for each of
these solutions, and use just this information to identify the optimal solution.
(b) Develop a table giving each of the CPF solutions and the corresponding
defining equations, BF solution. and nonbasic variables. Calculate Z for each of
these solutions, and use just this information to identify the optimal solution.
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activity additional algorithm amount analysis apply approach assignment assumed basic variable begin BF solution calculate called changes column complete Consider constraints Construct corresponding cost CPF solution customers decision demand described determine developed distribution entering equations estimated example expected feasible FIGURE first flow formulation given gives hour identify illustrate increase indicates initial inventory involves iteration linear programming machine Maximize mean million Minimize month needed node objective function obtained operations optimal optimal solution original parameter path plant player possible presented Prob probability problem procedure profit programming problem queueing respectively resulting shown shows side simplex method solution solve step strategy Table tableau tion transportation unit waiting weeks
Bibliographic information
| Title | Introduction to Operations Research, Volume 1 Introduction to Operations Research, Frederick S. Hillier McGraw-Hill series in industrial engineering and management science |
| Authors | Frederick S. Hillier, Gerald J. Lieberman |
| Edition | 7, illustrated |
| Publisher | McGraw-Hill, 2001 |
| Original from | the University of Michigan |
| Digitized | 8 Aug 2011 |
| ISBN | 0072416181, 9780072416183 |
| Length | 1214 pages |
| Export Citation | BiBTeX EndNote RefMan |