# A Mathematical Programming Language

A Mathematical Programming Language, aka A Mathematical Programming Language, is an actively used programming language created in 1985.

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- A Mathematical Programming Language ranks in the top 10% of languages
- the A Mathematical Programming Language website
- the A Mathematical Programming Language wikipedia page
- A Mathematical Programming Language first appeared in 1985
- the A Mathematical Programming Language team is on twitter
- See also: linux, unix, awk, c, algebraic-modeling-language, nl, xml, excel-app
- I have 70 facts about A Mathematical Programming Language. just email me if you need more.

### Example code from the web:

set PROD; # products param rate {PROD} > 0; # tons produced per hour param avail >= 0; # hours available in week param profit {PROD}; # profit per ton param market {PROD} >= 0; # limit on tons sold in week var Make {p in PROD} >= 0, <= market[p]; # tons produced maximize Total_Profit: sum {p in PROD} profit[p] * Make[p]; # Objective: total profits from all products subject to Time: sum {p in PROD} (1/rate[p]) * Make[p] <= avail; # Constraint: total of hours used by all # products may not exceed hours available

### Example code from Linguist:

# A toy knapsack problem from the LocalSolver docs written in AMPL. set I; param Value{I}; param Weight{I}; param KnapsackBound; var Take{I} binary; maximize TotalValue: sum{i in I} Take[i] * Value[i]; s.t. WeightLimit: sum{i in I} Take[i] * Weight[i] <= KnapsackBound; data; param: I: Weight Value := 0 10 1 1 60 10 2 30 15 3 40 40 4 30 60 5 20 90 6 20 100 7 2 15; param KnapsackBound := 102;

### Example code from Wikipedia:

set Plants; set Markets; # Capacity of plant p in cases param Capacity{p in Plants}; # Demand at market m in cases param Demand{m in Markets}; # Distance in thousands of miles param Distance{Plants, Markets}; # Freight in dollars per case per thousand miles param Freight; # Transport cost in thousands of dollars per case param TransportCost{p in Plants, m in Markets} := Freight * Distance[p, m] / 1000; # Shipment quantities in cases var shipment{Plants, Markets} >= 0; # Total transportation costs in thousands of dollars minimize cost: sum{p in Plants, m in Markets} TransportCost[p, m] * shipment[p, m]; # Observe supply limit at plant p s.t. supply{p in Plants}: sum{m in Markets} shipment[p, m] <= Capacity[p]; # Satisfy demand at market m s.t. demand{m in Markets}: sum{p in Plants} shipment[p, m] >= Demand[m]; data; set Plants := seattle san-diego; set Markets := new-york chicago topeka; param Capacity := seattle 350 san-diego 600; param Demand := new-york 325 chicago 300 topeka 275; param Distance : new-york chicago topeka := seattle 2.5 1.7 1.8 san-diego 2.5 1.8 1.4; param Freight := 90;Edit

Last updated February 11th, 2019