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SAMPL, which stands for "Stochastic AMPL", is an algebraic modeling language resulting by expanding the well-known language AMPL with extended syntax and keywords. It is designed specifically for representing stochastic programming problems and, through recent extensions, problems with chance constraints, integrated chance constraints and robust optimization problems. It can generate the deterministic equivalent version of the instances, using all the solvers AMPL connects to, or generate an SMPS representation and use specialized decomposition based solvers, like FortSP.

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  • SAMPL (en)
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  • SAMPL, which stands for "Stochastic AMPL", is an algebraic modeling language resulting by expanding the well-known language AMPL with extended syntax and keywords. It is designed specifically for representing stochastic programming problems and, through recent extensions, problems with chance constraints, integrated chance constraints and robust optimization problems. It can generate the deterministic equivalent version of the instances, using all the solvers AMPL connects to, or generate an SMPS representation and use specialized decomposition based solvers, like FortSP. (en)
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  • SAMPL (en)
name
  • SAMPL (en)
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code
  • buy[r] >= sum{p in Prod} ProdReq[r,p] * amountprod[p, s]; (en)
  • var amountprod{p in Prod, s in Scen} >= 0, (en)
  • var amountsell{p in Prod, s in Scen} >= 0, (en)
  • var buy{r in Resource} >= 0, (en)
  • production{p in Prod, s in Scen}: amountsell[p,s] <= amountprod[p,s]; (en)
  • budgetres: sum{r in Resource} Cost[r] * buy[r] <= Budget; (en)
  • sales{p in Prod, s in Scen}: amountsell[p,s] <= Demand[p,s]; (en)
designer
  • Gautam Mitra, Enza Messina, Valente Patrick (en)
genre
influenced by
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  • ampl (en)
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  • SAMPL, which stands for "Stochastic AMPL", is an algebraic modeling language resulting by expanding the well-known language AMPL with extended syntax and keywords. It is designed specifically for representing stochastic programming problems and, through recent extensions, problems with chance constraints, integrated chance constraints and robust optimization problems. It can generate the deterministic equivalent version of the instances, using all the solvers AMPL connects to, or generate an SMPS representation and use specialized decomposition based solvers, like FortSP. (en)
file ext
  • .mod .dat .run .sampl (en)
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  • 20120523
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