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Page 539
In general, the states are the various possible conditions in which the system
might be at that stage of the problem. The number of states may be either finite (
as in the stagecoach problem) or infinite (as in some subsequent examples).
In general, the states are the various possible conditions in which the system
might be at that stage of the problem. The number of states may be either finite (
as in the stagecoach problem) or infinite (as in some subsequent examples).
Page 556
... the preceding examples where there were only a few possible states to
consider. We now have an infinite number of possible states (240 < s3 = 255), so
it is no longer feasible to solve separately for x: for each possible value of s3.
Therefore ...
... the preceding examples where there were only a few possible states to
consider. We now have an infinite number of possible states (240 < s3 = 255), so
it is no longer feasible to solve separately for x: for each possible value of s3.
Therefore ...
Page 560
It only means that, instead of considering all possible values of the one state
variable, we must consider all possible combinations of values of the several
state variables. However, from the standpoint of computational efficiency, this
difference ...
It only means that, instead of considering all possible values of the one state
variable, we must consider all possible combinations of values of the several
state variables. However, from the standpoint of computational efficiency, this
difference ...
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Common terms and phrases
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 |