Genetic Algorithm Optimization Model for Central Marches Restoration Flows with Different Water Quality Scenarios

A Genetic Algorithm optimization model is used in this study to find the optimum flow values of Tigris river branches near Ammara city, which their water be for central marshes restoration after mixing Maissan River. These tributaries are Al-Areed, AlBittera and Al-Majar Al-Kabeer Rivers. The aim enhance quality River, hence provide acceptable marsh restoration. applied different change scenarios ,i.e. , 10%,20% increase EC,TDS BOD. output three rivers while, input data monthly flows(1994-2011),monthly requirements parameters (EC, TDS, BOD, DO pH).The objective function adopted a form sum difference each 5 parameters, resulting from themixing equation waters rivers, accepted limits these weighted by penalty factor assigned parameter according its importance. 1500,1000, 6,4 7, while factors 1,0.8,0.8,0.8,and 0.2 EC,TDS,BOD,DO,and pH respectively. constraints on decision variables flows those that demands downstream river, not exceed maximum flowlimits. cases, wet, average dry years. For case were values(scenario 1),the 10% EC,TDS, BOD (Scenario2),and 20% (Scenario 3). Hence nine cases an found river. genetic adopt variable number population 100 1000 step of100,0.8 cross over mutation rates, iterations reach stable solutions. results indicates analysis shows significant decrease rives year 2000,hence, period (1994-1999), excluded only (2000-2011). estimated exhibits low variation. observed general as changed wet normal cases. Scenarios S1 S2 S3 do necessarily all required values. obtained minimum functions certain trend with and/or scenarios.