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 129
First , all the tied basic variables reach zero simultaneously as the entering basic
variable is increased . Therefore , the one or ones not chosen to be the leaving
basic variable also will have a value of zero in the new BF solution . ( Note that ...
First , all the tied basic variables reach zero simultaneously as the entering basic
variable is increased . Therefore , the one or ones not chosen to be the leaving
basic variable also will have a value of zero in the new BF solution . ( Note that ...
Page 726
However , the focus in this chapter is on the simplest case , called two - person ,
zero - sum games . As the name implies , these games involve only two
adversaries or players ( who may be armies , teams , firms , and so on ) . They
are called ...
However , the focus in this chapter is on the simplest case , called two - person ,
zero - sum games . As the name implies , these games involve only two
adversaries or players ( who may be armies , teams , firms , and so on ) . They
are called ...
Page 1160
4 is strictly concave because its second second derivative always is less than
zero . As illustrated in Fig . A2 . 5 , any linear function has its second derivative
equal to zero everywhere and so is both convex and concave . The function in
Fig .
4 is strictly concave because its second second derivative always is less than
zero . As illustrated in Fig . A2 . 5 , any linear function has its second derivative
equal to zero everywhere and so is both convex and concave . The function in
Fig .
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Contents
SUPPLEMENT TO APPENDIX 3 | 3 |
Problems | 6 |
An Algorithm for the Assignment Problem | 18 |
Copyright | |
57 other sections not shown
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Common terms and phrases
activity additional algorithm allocation allowable amount apply assignment basic solution basic variable BF solution bound boundary calculations called capacity changes coefficients column complete Consider constraints construct corresponding cost CPF solution demand described determine direction distribution dual problem entering equal equations estimates example feasible FIGURE final flow problem Formulate 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 resource respective resulting revised Select shown shows side simplex method simplex tableau slack solve step supply Table tableau tion unit values weeks Wyndor Glass zero
Bibliographic information
| Title | Introduction to Operations Research McGraw-Hill International Editions McGraw-Hill industrial & plant engineering series 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 | Pennsylvania State University |
| Digitized | 26 Aug 2009 |
| ISBN | 0071181636, 9780071181631 |
| Length | 1214 pages |
| Export Citation | BiBTeX EndNote RefMan |