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Algorithms 2018,11, 54 Figure5.Strategicallocationofcommoncomponent inTestCase2. 2. ScenarioofBoundedRationalDecisionMaker The ordering quantities and profits under bounded rationality for test case 2 are reported inTable4. Table4.Orderingquantitiesandprofitsunderboundedrationality for test case2. CasesforBoundedRationalityConditionswithVaryingβParameter β Ordering Quantity in Market1 Ordering Quantity in Market2 Ordering Quantity in Market3 Ordering Quantity in Market4 Total Profits %Deviation fromAchievable Profits 0 1225 1263 923 1234 286,550 0.45 10 1232 1305 940 1258 262,834 1.53 100 1242 1360 1051 1264 213,850 2.24 1000 1335 1374 1066 1395 204,467 2.2 10,000 1409 1444 1066 1395 216,800 2.57 100,000 1462 1471 1066 1402 283,890 2.83 1,000,000 1500 1498 1075 1428 278,777 3.44 4.3. III.TestCase3 Problemsizen=10 1. ScenarioofUniformDemandDistribution X: Table5showstheproductionallocationvaluesof test case3. Table5.Productionallocationvalues for test case3. Market1 Market2 Market3 Market4 Market1 Market2 Market3 Market4 Market9 Market10 Plant1 1153 0 0 780 0 0 0 0 0 0 Plant2 0 593 782 0 0 0 0 543 0 0 Plant3 0 0 0 0 0 0 1472 0 0 0 Plant4 1673 0 0 0 0 0 0 0 0 0 Plant5 0 630 0 226 0 0 0 0 0 476 Plant6 1885 0 0 0 0 0 0 0 0 0 Plant7 0 252 378 150 0 0 0 474 0 720 139
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Algorithms for Scheduling Problems
Title
Algorithms for Scheduling Problems
Authors
Frank Werner
Larysa Burtseva
Yuri Sotskov
Editor
MDPI
Location
Basel
Date
2018
Language
English
License
CC BY 4.0
ISBN
978-3-03897-120-7
Size
17.0 x 24.4 cm
Pages
212
Keywords
Scheduling Problems in Logistics, Transport, Timetabling, Sports, Healthcare, Engineering, Energy Management
Categories
Informatik
Technik
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Algorithms for Scheduling Problems