###########################################################
# WDWR 18042                                              #
# Planowanie produkcj w warunkach ryzyka.                 #
# DANE                                                    #
# Autor: Krzysztof Rudnicki                                        #
###########################################################

# Narzedzia
set TOOLS := GRINDER VDRILL HDRILL MILLER LATHE;

# Miesiace
set MONTHS := JAN FEB MAR;

# Licza narzedzi
param toolCount :=
	GRINDER	4
	VDRILL	2
	HDRILL	3
	MILLER	1
	LATHE	1
	;

# Czasy produkcji h
param toolTimePerUnit:
				P1		P2		P3		P4 :=
	GRINDER		0.4		0.6		0		0	
	VDRILL		0.2		0.1		0		0.6
	HDRILL		0.1		0		0.7		0
	MILLER		0.06	0.04	0		0.05
	LATHE		0		0.05	0.02	0
	;
	
# Ograniczenia rynkowe liczby sprzedawanych produktow pcs
param salesMarketLimit:
			P1		P2		P3		P4	:=
	JAN		200		0		100		200
	FEB		300		100		200		200
	MAR		0		300		100		200
	;
	
# Ograniczeine liczby magazynowanych produktow pcs
param storageLimit := 
	P1	200
	P2	200
	P3	200
	P4	200
	;

# Koszt magazynowania produktow pln/pcs per month
param storageUnitCost := 1;

# Aktualny stan magazynowy pcs
param startingStorage :=
	P1	0
	P2	0
	P3	0
	P4	0
	;
	
# Poz�dany stan magazynowy na koniec marca pcs
param desiredEndStorage :=
	P1	50
	P2	50
	P3	50
	P4	50
	;

# Liczba dni roboczych w miesiacu d
param daysPerMonth := 24;

# Liczba zmian w ciagu jednego dnia roboczego
param shiftsPerDay := 2;

# Dlugosc zmiany h
param hoursPerShift := 8;

# Zyski warto�� oczekiwana
param expectedProfitPerUnit :=
	P1	8.50944172786882
	P2	8.47100593224391
	P3	8.1319049712769
	P4	6.39446520538826
	;
	
# Metoda punktu odniesienia
param epsilon = 0.000025;

param beta = 0.001; 

param utopia :=
 	PROFIT 	11987
 	RISK	0
 	; 
 	
param nadir :=
	PROFIT	-2400
	RISK	2815
	;

# Scenariusze
param scenarioCount := 50;
param scenarioProfitPerUnit:
			P1					P2					P3					P4 := 
	1		 6.78312108289149	 5.79640238361981	10.05787433056357	 6.57331416435723
	2		 6.99738290528301	 9.01490464757196	 5.08481517735633	 6.42703739335277
	3		 5.16730304787176	 7.52317923266688	10.72313438657665	 7.22667916959417
	4		 8.52274093276464	11.38240217987188	 6.13080610568167	 6.43883854824552
	5		 6.50428131735901	 6.61788006135640	 7.86111017073128	 6.96225068464523
	6		 5.73487133076911	 9.16374087573468	 5.52557377604414	 6.34042770048443
	7	 	 7.57821826531473	 5.53212159376577	 9.44747152703083	 7.92080735281354
	8		 8.46351060213176	 6.67108340536348	 7.96447972290298	 6.74037823409959
	9		10.60705431897493	 6.29351506828248	 8.08238578885269	 6.64513805083938
	10		 5.49788635095338	 8.01657169352075	 8.50721094756387	 6.32347360999400
	11	 	 9.98722514505514	 8.89045419912165	 7.40638427340367	 6.19123907839219
	12	 	 7.73547221322455	11.39341677791569	 7.08591860802534	 6.65287015880773
	13	 	 8.00244141512299	 7.46013718525416	 9.07534043801771	 7.01972409076348
	14		10.01757296285428	11.16631823758034	 5.36427432741987	 5.93803320930752
	15	 	 8.73982030016946	 7.22788862315047	 7.52123044637611	 6.30583102048732
	16	 	 6.74830998356361	 5.16961378121024	 9.83052665533391	 6.97518295642799
	17	 	 5.79891835909540	 7.62305645016980	 7.28259746189341	 6.58122366239758
	18	 	 5.01746785364914	 5.37120611569365	11.37580509674048	 7.45754618734148
	19		 8.84615981059243	10.36884740288172	 5.51512168506823	 5.14746695259905
	20		10.27832406220036	 6.26817737098193	 6.75980452880535	 6.00071122161820
	21		 9.15464079326701	 9.22511946737560	 8.59742728186919	 5.85941844163078
	22		 7.41070715265531	 9.03326860943882	 9.51105396612463	 5.95705526059528
	23		 9.41688054404721	 5.48792302160852	 8.05314441506622	 6.33167522079485
	24		 7.99636302963949	 8.45127363831087	 6.80178566896807	 6.40796549415317
	25		 8.77607512859202	 9.06083514509964	 6.14324653925151	 5.73196891114116
	26		 6.15756683330483	 5.81155622391928	 8.95298231122791	 7.75631798464974
	27		 8.71820952681711	 6.75933713868641	 6.20173677287384	 5.94931057772569
	28		 7.50988798239200	 8.40250942598753	 7.59076793688675	 6.83115118367424
	29		11.46519479939599	 5.34788729417893	 7.49642151003498	 5.09135446750897
	30		 9.24470379243678	 7.86407386582905	 6.91504065225354	 5.66423375179536
	31		10.11059443261933	 5.19726478862852	 7.17323727021490	 5.35589059533840
	32		 8.52798709174698	 9.92750815054074	 7.11656712470230	 5.52054849939254
	33		10.96107079994176	 7.10910792528864	 5.70378349251154	 5.17164984043314
	34		 7.06917204470777	 7.93024674036222	 7.04742602521247	 6.02267636557175
	35		 8.48134255283988	 5.85227829193417	 5.36851422694765	 6.58963142694151
	36		10.79598232218280	 6.78064186807628	 6.45254214496221	 6.01773663687229
	37		 9.31085304521786	 7.24038452979960	 7.11927599287817	 5.94495349693440
	38		11.73162984938600	 8.89170449659670	 7.24145427728390	 5.50727529989226
	39		 9.95614904957837	 8.24343617183020	 6.08421773053824	 5.59097741826648
	40		10.84398291202468	 5.62144717550252	 8.73978776370006	 5.90011906694585
	41		 9.66329756207950	 8.71563915673125	 8.57471405154024	 6.25399915313449
	42		11.75197973817904	 9.62791703809340	 6.15087294856069	 5.12525411655807
	43		10.21024933655283	 5.45043424512963	 7.70802205088631	 6.26487953122650
	44		 7.00126415308046	 9.52080591709321	 6.34678934922762	 5.78571635562224
	45		10.95808951943000	 5.38346727815726	 6.12050483571891	 7.52568971146160
	46		 7.24407146573199	10.74100159223745	 7.79352388695434	 5.86675126000469
	47		11.09420218544564	 7.58722148021949	10.11955301735720	 5.87263773263194
	48		 6.56196505922266	 8.86557049389506	 6.68759866488725	 6.54786762414447
	49		 6.36408747696432	 9.90697341186375	 8.67549323089252	 7.10602003316923
	50		 5.25413960261441	 9.86316602732531	 6.97502397729463	 5.79670081684910
	;