## Introduction to Operations Research, Volume 1-- This classic, field-defining text is the market leader in Operations Research -- and it's now updated and expanded to keep professionals a step ahead -- Features 25 new detailed, hands-on case studies added to the end of problem sections -- plus an expanded look at project planning and control with PERT/CPM -- A new, software-packed CD-ROM contains Excel files for examples in related chapters, numerous Excel templates, plus LINDO and LINGO files, along with MPL/CPLEX Software and MPL/CPLEX files, each showing worked-out examples |

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Page 214

0 – 1 1 Rows 1 to 3 of the initial

0 | 12|, 3 2 : 0 0 1 #18 where the third, fourth, and fifth columns (the coefficients of

the slack variables) form an identity matrix. Therefore, - - 1 0 1 0 1 1 0 0 4 New ...

0 – 1 1 Rows 1 to 3 of the initial

**tableau**are 1 0 1 0 0 4 Old rows 1–3 = | 0 2 : 0 10 | 12|, 3 2 : 0 0 1 #18 where the third, fourth, and fifth columns (the coefficients of

the slack variables) form an identity matrix. Therefore, - - 1 0 1 0 1 1 0 0 4 New ...

Page 216

... the initial

row 0–[0, 3. 1]. This calculation is shown below, where the first vector is row 0 of

the initial

... the initial

**tableau**by using just the coefficients of the slack variables in the finalrow 0–[0, 3. 1]. This calculation is shown below, where the first vector is row 0 of

the initial

**tableau**and the matrix is rows 1 to 3 of the initial**tableau**. 1 0 1 0 0 4 ...Page 259

These coefficients of the slack variables necessarily are unchanged with the

same algebraic operations originally performed by the simplex method because

the coefficients of these same variables in the initial

These coefficients of the slack variables necessarily are unchanged with the

same algebraic operations originally performed by the simplex method because

the coefficients of these same variables in the initial

**tableau**are unchanged.### What people are saying - Write a review

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activity additional algorithm alternative amount analysis apply assignment assumed basic variable begin BF solution 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 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 waiting weeks