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 941
checked at discrete intervals , e.g. , at the end of each week , and ordering
decisions are made only at these times even if the inventory level dips below the
reorder point between the preceding and current review times . ( In practice , a ...
checked at discrete intervals , e.g. , at the end of each week , and ordering
decisions are made only at these times even if the inventory level dips below the
reorder point between the preceding and current review times . ( In practice , a ...
Page 951
One form of waste is unnecessary inventory . Others are unnecessarily large
setup costs , unnecessarily long lead times , production facilities that are not
operational when they are needed , and defective items . Minimizing these forms
of ...
One form of waste is unnecessary inventory . Others are unnecessarily large
setup costs , unnecessarily long lead times , production facilities that are not
operational when they are needed , and defective items . Minimizing these forms
of ...
Page 984
Multiechelon Inventory Systems Our growing global economy has caused a
dramatic shift in inventory management entering the 21st century . Now , as never
before , the inventory of many manufacturers is scattered throughout the world .
Multiechelon Inventory Systems Our growing global economy has caused a
dramatic shift in inventory management entering the 21st century . Now , as never
before , the inventory of many manufacturers is scattered throughout the world .
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Common terms and phrases
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 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