GLSP Instances

Published: 23 August 2017| Version 1 | DOI: 10.17632/tm5kj48jfg.1
Contributors:
Eduardo Curcio,
,

Description

There are 23 instances for OPL based models: - 5 instances with 3 products, 3 periods and low production capacity (cp=0.9) - 5 instances with 3 products, 3 periods and high production capacity (cp=0.75) - 5 instances with 3 products, 3 periods and low production capacity (cp=0.9) - 5 instances with 3 products, 3 periods and high production capacity (cp=0.75) - 3 instances with 7 products, 8 periods and low production capacity (cp=0.9) There are complementary instances for stochastic programming models: - For the two-stage stochastic programming with 10, 50, 100, 200 and 500 scenarios - For the multistage stochastic programming with 12, 20, 30, 39, 42, 110, 155, 240, 258, 399, 420 and 584 nodes - Remarks: 1) the number of nodes depends on the size of instances. 2) there are instances with small number of nodes that were not considered in the computational experiment. Characteristics of instances: --- General --- P -> Number of Products T -> Number of Periods // " "-> Coeficient of variation (for simulation purposes) M -> Number of Microperiods P_Cap -> Production capacity P_BigM -> "BigM" P_Productiontime -> Production time P_MinimumLot -> Minimum lotsize P_HoldingCost -> Holding cost P_ShortageCost -> Shortage cost P_InitialInventory -> Initial inventory P_InitialBacklog -> Initial backlog P_SetupCost -> Setup costs P_SetupTime -> Setup time P_MaximummLot -> Maximum lotsize Microperiods2 -> Parameter relating microperiods to periods --- Two-stage stochastic programming parameters --- K -> Number of scenarios P_Probability -> Probability of scenario realization P_SetupTimeS -> Setup time per scenario (NOT USED) P_ProductiontimeS -> Production time per scenario (NOT USED) P_DemandS -> Demand realization for a given scenario --- Multistage stochastic programming parameters --- N -> Number of nodes P_Probability -> Probability of node realization Period -> Parameter relating a node to a period PreNode -> Parameter relating a node to its predecessor P_DemandS -> Demand realization for a given node

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Optimization (Algorithms), Operations Research, Lot Sizing

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