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 102
Then use the Excel Solver to solve the model, c (c) Use MPL to formulate this
model in a compact form. Then use the MPL solver CPLEX to solve the model. C
(d) Use LINGO to formulate this model in a compact form. Then use the LINGO ...
Then use the Excel Solver to solve the model, c (c) Use MPL to formulate this
model in a compact form. Then use the MPL solver CPLEX to solve the model. C
(d) Use LINGO to formulate this model in a compact form. Then use the LINGO ...
Page 178
(a) Solve this problem graphically. (b) Using the Big M method, construct the
complete first simplex tableau for the simplex method and identify the
corresponding initial (artificial) BF solution. Also identify the initial entering basic
variable and ...
(a) Solve this problem graphically. (b) Using the Big M method, construct the
complete first simplex tableau for the simplex method and identify the
corresponding initial (artificial) BF solution. Also identify the initial entering basic
variable and ...
Page 640
(b) Use this algorithm to solve this problem. 12.6-9.* Consider the following
nonlinear BIP problem. Z = 80*, + 60x2 + 4(k3 + 20t4 - (7*1 + 5jc2 + 3*3 + 2*4)2,
fory'= 1,2,3,4. Maximize subject to Xj is binary. Given the value of the first k
variables ...
(b) Use this algorithm to solve this problem. 12.6-9.* Consider the following
nonlinear BIP problem. Z = 80*, + 60x2 + 4(k3 + 20t4 - (7*1 + 5jc2 + 3*3 + 2*4)2,
fory'= 1,2,3,4. Maximize subject to Xj is binary. Given the value of the first k
variables ...
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Contents
SUPPLEMENT TO APPENDIX 3 | 3 |
Problems | 6 |
An Algorithm for the Assignment Problem | 18 |
Copyright | |
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Common terms and phrases
activity additional algorithm alternative amount analysis apply assigned assumed basic variable begin BF solution bound calculate called changes coefficients column complete Consider constraints Construct corresponding cost CPF solution customers decision demand described determine developed distribution entering equations estimated example expected feasible FIGURE final flow formulation given gives hour identify illustrate increase indicates initial inventory iteration linear programming machine Maximize maximum mean million Minimize month needed node objective function obtained operations optimal optimal solution original parameter path payoff perform 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 weeks
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 |