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https://github.com/kuhyx/WUT_Computer_Science.git
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154 lines
5.6 KiB
Plaintext
154 lines
5.6 KiB
Plaintext
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###########################################################
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# WDWR 18042 #
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# Planowanie produkcj w warunkach ryzyka. #
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# DANE #
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# Autor: Krzysztof Rudnicki #
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###########################################################
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# Narzedzia
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set TOOLS := GRINDER VDRILL HDRILL MILLER LATHE;
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# Miesiace
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set MONTHS := JAN FEB MAR;
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# Licza narzedzi
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param toolCount :=
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GRINDER 4
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VDRILL 2
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HDRILL 3
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MILLER 1
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LATHE 1
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;
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# Czasy produkcji h
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param toolTimePerUnit:
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P1 P2 P3 P4 :=
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GRINDER 0.4 0.6 0 0
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VDRILL 0.2 0.1 0 0.6
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HDRILL 0.1 0 0.7 0
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MILLER 0.06 0.04 0 0.05
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LATHE 0 0.05 0.02 0
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;
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# Ograniczenia rynkowe liczby sprzedawanych produktow pcs
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param salesMarketLimit:
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P1 P2 P3 P4 :=
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JAN 200 0 100 200
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FEB 300 100 200 200
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MAR 0 300 100 200
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;
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# Ograniczeine liczby magazynowanych produktow pcs
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param storageLimit :=
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P1 200
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P2 200
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P3 200
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P4 200
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;
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# Koszt magazynowania produktow pln/pcs per month
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param storageUnitCost := 1;
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# Aktualny stan magazynowy pcs
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param startingStorage :=
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P1 0
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P2 0
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P3 0
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P4 0
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;
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# Poz<6F>dany stan magazynowy na koniec marca pcs
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param desiredEndStorage :=
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P1 50
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P2 50
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P3 50
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P4 50
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;
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# Liczba dni roboczych w miesiacu d
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param daysPerMonth := 24;
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# Liczba zmian w ciagu jednego dnia roboczego
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param shiftsPerDay := 2;
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# Dlugosc zmiany h
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param hoursPerShift := 8;
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# Zyski warto<74><6F> oczekiwana
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param expectedProfitPerUnit :=
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P1 8.50944172786882
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P2 8.47100593224391
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P3 8.1319049712769
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P4 6.39446520538826
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;
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# Metoda punktu odniesienia
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param epsilon = 0.000025;
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param beta = 0.001;
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param utopia :=
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PROFIT 11987
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RISK 0
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;
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param nadir :=
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PROFIT -2400
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RISK 2815
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;
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# Scenariusze
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param scenarioCount := 50;
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param scenarioProfitPerUnit:
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P1 P2 P3 P4 :=
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1 6.78312108289149 5.79640238361981 10.05787433056357 6.57331416435723
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2 6.99738290528301 9.01490464757196 5.08481517735633 6.42703739335277
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3 5.16730304787176 7.52317923266688 10.72313438657665 7.22667916959417
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4 8.52274093276464 11.38240217987188 6.13080610568167 6.43883854824552
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5 6.50428131735901 6.61788006135640 7.86111017073128 6.96225068464523
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6 5.73487133076911 9.16374087573468 5.52557377604414 6.34042770048443
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7 7.57821826531473 5.53212159376577 9.44747152703083 7.92080735281354
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8 8.46351060213176 6.67108340536348 7.96447972290298 6.74037823409959
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9 10.60705431897493 6.29351506828248 8.08238578885269 6.64513805083938
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10 5.49788635095338 8.01657169352075 8.50721094756387 6.32347360999400
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11 9.98722514505514 8.89045419912165 7.40638427340367 6.19123907839219
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12 7.73547221322455 11.39341677791569 7.08591860802534 6.65287015880773
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13 8.00244141512299 7.46013718525416 9.07534043801771 7.01972409076348
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14 10.01757296285428 11.16631823758034 5.36427432741987 5.93803320930752
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15 8.73982030016946 7.22788862315047 7.52123044637611 6.30583102048732
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16 6.74830998356361 5.16961378121024 9.83052665533391 6.97518295642799
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17 5.79891835909540 7.62305645016980 7.28259746189341 6.58122366239758
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18 5.01746785364914 5.37120611569365 11.37580509674048 7.45754618734148
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19 8.84615981059243 10.36884740288172 5.51512168506823 5.14746695259905
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20 10.27832406220036 6.26817737098193 6.75980452880535 6.00071122161820
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21 9.15464079326701 9.22511946737560 8.59742728186919 5.85941844163078
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22 7.41070715265531 9.03326860943882 9.51105396612463 5.95705526059528
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23 9.41688054404721 5.48792302160852 8.05314441506622 6.33167522079485
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24 7.99636302963949 8.45127363831087 6.80178566896807 6.40796549415317
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25 8.77607512859202 9.06083514509964 6.14324653925151 5.73196891114116
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26 6.15756683330483 5.81155622391928 8.95298231122791 7.75631798464974
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27 8.71820952681711 6.75933713868641 6.20173677287384 5.94931057772569
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28 7.50988798239200 8.40250942598753 7.59076793688675 6.83115118367424
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29 11.46519479939599 5.34788729417893 7.49642151003498 5.09135446750897
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30 9.24470379243678 7.86407386582905 6.91504065225354 5.66423375179536
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31 10.11059443261933 5.19726478862852 7.17323727021490 5.35589059533840
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32 8.52798709174698 9.92750815054074 7.11656712470230 5.52054849939254
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33 10.96107079994176 7.10910792528864 5.70378349251154 5.17164984043314
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34 7.06917204470777 7.93024674036222 7.04742602521247 6.02267636557175
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35 8.48134255283988 5.85227829193417 5.36851422694765 6.58963142694151
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36 10.79598232218280 6.78064186807628 6.45254214496221 6.01773663687229
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37 9.31085304521786 7.24038452979960 7.11927599287817 5.94495349693440
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38 11.73162984938600 8.89170449659670 7.24145427728390 5.50727529989226
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39 9.95614904957837 8.24343617183020 6.08421773053824 5.59097741826648
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40 10.84398291202468 5.62144717550252 8.73978776370006 5.90011906694585
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41 9.66329756207950 8.71563915673125 8.57471405154024 6.25399915313449
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42 11.75197973817904 9.62791703809340 6.15087294856069 5.12525411655807
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43 10.21024933655283 5.45043424512963 7.70802205088631 6.26487953122650
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44 7.00126415308046 9.52080591709321 6.34678934922762 5.78571635562224
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45 10.95808951943000 5.38346727815726 6.12050483571891 7.52568971146160
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46 7.24407146573199 10.74100159223745 7.79352388695434 5.86675126000469
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47 11.09420218544564 7.58722148021949 10.11955301735720 5.87263773263194
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48 6.56196505922266 8.86557049389506 6.68759866488725 6.54786762414447
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49 6.36408747696432 9.90697341186375 8.67549323089252 7.10602003316923
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50 5.25413960261441 9.86316602732531 6.97502397729463 5.79670081684910
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;
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