CS1181-Project3 CS 1181 Programming Project 3 CS 1181 Project 3: Data Science (Grocery Store Simulation) PURPOSE: This assignment explores simulation of a real world situation which leads to...

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CS1181-Project3.pdf file is the assignment, the zip file is to be used in it.


CS1181-Project3 CS 1181 Programming Project 3 CS 1181 Project 3: Data Science (Grocery Store Simulation) PURPOSE: This assignment explores simulation of a real world situation which leads to meaningful actions to solve a problem. A very common use of computers is to run simulations to answer practical questions with no easy closed-form mathematical solution. A simulation is a program designed to model a real system of interest. By setting parameters and selecting an appropriate model, results are produced that model the behavior of the real system. If the model is a valid representation of the real system, then the simulation can even predict the future performance of the real system. PROBLEM: In this project, you will construct a program to optimize efficiency of a grocery store. Your goal is to use your simulation to answer a specific question. A grocery store currently has 12 checkout lanes. Some of those lanes allow customers to purchase any number of items. Some of the lanes are ‘express lanes’, which only allow customers who are purchasing twelve items or less. If our goal is to minimize the overall time that customers wait in line, how many of our 12 lanes should be express lanes? Assume that we collected data from a ‘normal/average’ set of customers during a normal/average day of operation. We observe the customers and determine that they are characterized by: (1) Time of arrival at the store (in minutes relative from the store opening) (2) Their order size (the number of items that they purchase) (3) The average time it takes for them to select each grocery item (their total time spent browsing divided by their order size) We provide this information in a text file. Each customer is one line of the data file, characterized by these three measurements in that order. For example, the line “2.0 15 0.5” in the data file represents a customer that arrives at the store 2.0 minutes after the store opens. The customer picks up 15 items and on average takes 0.5 minutes to pick up each item. The customer therefore spends 15 * 0.5 = 7.5 minutes shopping and then is ready to check out at 9.5 minutes after the store opens. The customer then moves to the checkout area. We will assume that customers will always select the checkout area with the shortest number of other customers in line (no matter how many items those customers are purchasing). Customers with more than 12 items can only use the regular checkout lanes. Customers with 12 or fewer items can use any lane. If there is a tie in line length, then customers will select any of the lines of equal length. Customers with 12 or fewer items will select an express lane over a regular lane if the two lanes are tied in the length of their line. If there is no one in line for a checkout lane, then the customer can immediately begin checking out. If there is anyone in line, then the customer must wait for everyone in front of them in their line to check out before they can begin to check out. The time to check out is determined by the characteristics of the type of lane (regular or express) and the size of the order. Regular lanes have an average checkout time of 0.05 minutes per item in the order plus 2.0 minutes to process payment and coupons. Express lanes have an average checkout time of 0.10 minutes per item in the order plus 1.0 minutes to process payment and coupons. Continuing the example, our customer with 15 items moves to check out at 9.5 minutes after the store opens. Since they have 15 items, they must use a regular checkout lane. They select the checkout lane with the shortest line. Let us assume that there is a regular checkout lane with no line (0 wait time). They immediately begin to check out. The time to check out is 15 (items) * 0.05 (minutes per item) + 2.0 (minutes to process payment) = 2.75 minutes. The customer leaves the store at 12.25 minutes after the store opens (9.5 min arrival at checkout + 0 wait + 2.75 minute checkout). If all lanes had at least one customer already in the lane, then our example customer could not begin to check out until every customer in line in front of them had first completed _their_ checkout. We will use a discrete event simulation to simulate the grocery store. This means time is managed by using a simulation clock that is advanced whenever an interesting event occurs. For example, if the simulation time is 0.0 minutes and a customer enters the store at a time 2.0 minutes, we mark the passage of time by advancing the simulation clock to 2.0 | P a g e 1 CS 1181 Programming Project 3 minutes (current time = 0.0 + time of arrival event = 2.0). If a customer reaches a checkout line 7.5 minutes later, we advance the simulation clock to 9.5 (2.0 + 7.5). Our assumption is no interesting activities occur between events (i.e. nothing significant happens in the intervals (0.0, 2.0) or (2.0, 9.5) so we can record the passage of time by moving the simulation clock forward to the time when the next important event occurs). The diagram shown below outlines the flow of events in our simulation. To begin, set the simulation clock to 0.0 and schedule the first customer arrival. We place each new event on a list (a priority queue might be a good choice) that contains the sequence of pending activities ordered by increasing simulation time. The actions associated with our example customer are (1) create customer object containing the customer’s data and (2) schedule the customer’s arrival. The setup after scheduling the first customerArrival event might appears as follows: simClock = 0.0 event list = ( {2.0, customer 1 arrives} // other customers/events not shown – the event list should start with all customer arrivals! ) To process an event, simply remove the first event from the list, update the simulation clock to the time of the event and perform the action needed to simulate the event. After removing the event the list appears as follows: simClock = 2.0 Note simulation time has advanced to the time of the event event list = ( // other customer/events not shown ) Since the first event is an arrival, perform the actions associated with a new arrival. This customer is selecting 15 items and will take an average of 0.5 minutes to select each item so you will need to schedule an end shopping event for this customer in 15 * 0.5 = 7.5 minutes. Now the event list looks like this: simClock = 2.0 event list = ( {9.5, customer 1 done shopping}, // other customer/events not shown ) Customer Arrival Event Customer End Shopping Customer End Checkout Customer has arrived – schedule the next arrival Customer starts shopping– schedule this customer to end shopping Customer ends shopping – put the customer in a checkout line and if he/she is the first in line schedule this customer to end checkout Customer ends checkout – if another customer is wai;ng in line, schedule the next customer to end checkout | P a g e 2 CS 1181 Programming Project 3 Events will be processed in scheduled ‘time’ order… there may be other customer arrivals or other events before our example customer 1 is done shopping. When their ‘event’ is next, then we will remove them from event list and assign them to a lane. simClock = 9.5 event list = ( // other customer/events not shown… for the example we will assume that one of them is // using our assigned lane until 10.0 ) If that lane is full, then we place that customer/event in a queue for that lane. Eventually they will get to the front of their checkout line at which point we can schedule their checkout. For this example, we will assume that they were assigned to checkout lane #3 and that the person ‘in front’ of them finishes _their_ checkout at time 10.0 minutes after the store opens. Now that they are at the head of the checkout line, we start their checkout by scheduling its completion. simClock = 10.0 event list = ( {12.75, customer 1 done with checkout} // other customer/events not shown ) simClock = 12.75 event list = ( // other customer/events not shown ) Once the customer completes checkout then we have finished processing that customer. We remove them from the event queue and check to see if there is anyone behind them in their checkout lane. If there is, then we’ll schedule that next customer for checkout. We might want to save the customer to provide data to calculate statistics at the end of the simulation. To summarize, the actions to perform for each event are: customerArrival -- When an arrival occurs, create a
Answered 15 days AfterOct 14, 2021

Answer To: CS1181-Project3 CS 1181 Programming Project 3 CS 1181 Project 3: Data Science (Grocery Store...

Ayush answered on Oct 30 2021
132 Votes
Grocery-Store-Simulation-master/GroceryStore/project/Arrival.txt
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173.2276281088113      5      1.2943577097191952
420.0142170517891      10      0.8469666833195222
535.9689264827181      3      1.900943902664826
645.5339370711242      8      1.6726074718530572
353.41029072119227      11      1.249256683649396
407.4227037897732      1      0.1131282819379742
210.1105309477669      2      0.8180929157263241
875.3849905684667      2      1.9238407326108653
916.4620883099457      11      0.6866403487436461
706.2240438138663      1      0.6211940971786529
362.3046781467847      6      0.2344925634409074
350.4130571068135      5      0.5917912040932589
919.2812001098047      10      0.3381283582683279
252.14387288754781      10      1.835834694917358
273.5832317864948      6      0.4836185856423907
935.4612481898668      10      1.9213101000001933
144.84140829069307      9      1.1588728550145266
771.1110321035063      7      0.8234871550657532
169.36167340458246      6      0.27894649362998436
595.5077659783296      5      0.04600745229549963
949.1759525402953      4      1.1742379734910504
798.3792446626682      4      0.18875532038257603
563.1511223616504      9      0.8670362333624502
634.364960861113      10      0.711457134409208
813.323441635735      10      0.6037644745640129
708.6555310952541      7      0.6518485486836954
818.0401124315545      7      1.619126189335768
287.26200996631707      1      1.4483707690613012
798.1886568324346      11      0.19863727625062788
67.12529952107877      9      0.588532020382218
149.78182950025862      11      0.6859308932596957
634.0241378306731      3      1.6978755518422584
745.3883434594879      4      0.1527016978085396
19.449918727660695      6      1.887263044079915
213.0162864271832      9      1.1079154432124951
286.7017700824832      6      1.0179865806100006
415.1733582345909      7      0.5584043654763629
513.6557814906232      9      0.19889232203380236
104.25862918316112      3      1.7283980784199853
444.7982297104412      1      0.8148152939015871
347.44826475415977      7      1.1778596952517706
788.3326645554916      2      0.06251130110952041
441.79033166423704      9      1.399409221268139
934.6966539504737      7      1.0440100163290422
645.7436614061427      8      0.2855741150322604
803.7146189387046      7      1.4867310136545
120.50401795902489      2      0.3003154195939024
812.4963139236469      6      0.01737711032090572
387.73842847267      11      1.5131860029779376
454.0278222756494      7      0.34887893156777516
141.07179215044832      6      1.7067928461493957
13.23142906002686      2      0.8265850006307136
164.57580781396217      10      1.9879089696075574
562.9582800270096      7      0.44530633253438956
825.5320715026287      5      1.2528140737250264
463.3681574499038      11      1.9603053905283538
549.7716515867335      6      0.6051933096186142
854.215402213236      8      0.18419878109459642
122.52255246350515      10      0.6208902866778929
144.55136672018716      11      0.4431004690429392
784.9725379384963      5      0.0124486229965719
788.9483793764379      4      1.7579878242093447
608.9243180020454      9      0.6758879588688989
164.8068207713559      11      1.2638170784672285
120.1882380308217      11      1.8044998430543144
52.2088064276185      6      1.1656637121485591
661.62669160258      7      1.3253187350088897
345.7940835221851      5      0.9882017104005896
568.3946864217558      6      1.5427750989001106
116.74518450537107      6      1.6759930201458861
19.473428925480068      2      1.8440781645120135
447.25072740533415      7      0.26490481037668
492.5834425293291      4      0.5090540148188916
821.1647838700275      10      1.2308471727984782
740.2066836602476      4      0.044187315885403367
400.4715281394562      10      1.4359938907800223
428.41736183058487      11      0.5909314605636233
794.9029885616679      4      1.8835517273286349
164.38943341705954      1      1.5001702215762829
670.5237986215207      2      1.6525503365225798
777.644380201912      1      1.3699811797181891
853.5019239150959      2      0.6503696183915981
182.85558904440506      4      1.058276945446253
915.9152932877741      1      0.7728755077235616
295.31818076031885      11      0.34493104191337753
108.41820511961626      9      0.12393372065703123
7.2127945978694505      9      0.0628412383916026
644.6017706469133      7      0.8852873053539072
106.67851763836596      1      0.2709899881947895
9.95328145489873      10      1.8556477877243989
113.30486926214226      3      0.1256394671830232
396.5484648214545      11      0.54943932213496
466.25398639089974      9      1.8327952625930641
764.9305156477241      2      1.8597787061477642
577.3290182959993      3      1.84419510846261
500.5430152974265      9      1.7895496647899622
316.3656846439702      9      1.292275846223604
704.4291018621528      6      1.625164230222797
273.4969045317395      5      0.6425529483939829
492.59742357713156      6      1.4998780246542294
30.733685558014308      2      1.3640571132772021
157.22844701137586      3      1.7411654336343372
368.7294254312694      7      1.8631225429925156
501.07197419431174      2      1.2372441183638154
65.31573520155831      4      1.3698589155666636
776.6151318345331      4      0.6526952927518059
618.8823831177494      4      1.3807712498288043
135.60670476445966      10      0.37733252661958594
803.8437416279263      2      1.7096680309370536
169.8596881809161      1      0.1548574709545516
10.412222695393378      11      0.3404240594842993
802.0539347753229      4      1.300983323060978
442.76381828656423      9      1.8612940648637322
500.9827773761465      7      0.020934262206856902
458.21159163959345      6      1.1370046773663105
748.8704948527      7      1.6536197300935525
505.43373574025753      11      0.4812454441505023
799.397130528313      5      0.6281632782765549
6.568967185188211      3      0.46163311151582453
456.8488509877215      5      1.785418043061287
173.48530848512755      8      0.728690755730057
547.6363305591667      5      0.6039478576056869
153.83935368732796      9      0.13056975391328862
846.6435778031647      5      1.2317781289969536
400.2186980448444      11      1.6705989614513546
555.6614910561873      4      0.36084807965306775
518.4503952921315      3      1.4934769396661969
949.2829868887939      7      0.5331051995427252
958.7625356791782      8      1.5499795143786625
556.1734763059231      9      1.9219026635248617
89.31312471716676      2      0.48514550151188796
771.7455463850033      7      1.8198679915197205
108.50558577139145      2      0.8104720506758387
957.9510813810571      5      0.6585350065416711
891.5566757803439      10      1.8399123733934055
600.7263361197146      10      1.4033497476331132
577.9850136383508      10      0.06936334546753464
551.4846366544679      2      1.471500309547454
481.7637690621035      6      0.6305735416867362
200.92115473026533      4      0.11446401391624472
487.00054545208724      10      0.7174371375982771
213.0796889911872      9      0.5410329656772805
707.5460359209751      11      1.1236747449858597
1.5142596584083736      8      0.32245748458115986
524.2156854733074      10      1.4978909622065129
957.1670850887474      4      0.055557495827622816
102.36843414383178      9      0.960639836152972
57.07024917506299      1      0.4422779260110963
235.90435757122412      11      1.27788161256364
720.7732979383508      9      1.299028631528881
544.0068849210328      10      0.8792765940448937
496.7015877666228      11      0.3038366159246859
523.8047643235069      1      0.27508984669753467
78.97935267087014      7      1.1351695055258408
838.9054407021824      6      0.5827749735849728
568.2105751040698      3      0.00834835737755757
898.2529224602993      7      1.2380220922636693
628.7262796638689      7      0.27258050746497253
864.9875621423027      4      1.9433943683243378
52.88746419940857      1      0.8363855860588572
479.88355147696757      4      0.5025961188511756
637.5121229255479      2      0.7278938555634831
340.16999679419644      1      1.4956113759099405
878.7867753783622      5      1.3992357276368508
633.2097498611215      9      0.4588845296724069
316.36818838932686      6      0.6248519939238018
581.9283984968862      3      1.1285802017155806
662.599171447112      3      1.53960424002302
890.3199746325182      9      1.7607191831496478
727.0009157158909      8      0.875392234712199
294.77120455227634      1      1.030334195715674
104.68865656553085      6      0.48965927612541793
539.7676182149966      6      1.5971874745843355
263.1415559838071      6      0.3845212438000545
900.3905400448059      7      0.2662363046519649
445.47332225467886      6      0.48386619543800746
702.4680212939887      11      1.5188783849189398
438.9567784959554      6      0.20396787220510548
596.5789888258643      7      1.891763548079791
922.092274340591      8      0.401014307302513
556.0664161162595      2      0.6730665993116065
561.8417135614352      8      0.5303053244893734
168.72614358403487      2      1.2047895990639077
426.222563301987      11      0.07429019176708218
437.7932744387747      3      1.8508489748280055
7.040406646039294      9      1.6014357855306445
715.8411094564998      6      1.6351061448107544
716.9868928413003      10      0.6602065734303695
559.2840819094919      10      0.4855768830127285
110.31929909003156      11      0.3910361538779912
208.58458617628193      9      0.8490042970713605
587.126226305752      7      1.8966470292336866
438.2061324063651      2      0.6657557308647757
93.35576122888129      8      1.5337636615437527
105.73950793499345      7      1.9143126780069402
635.0013336208789      1      1.2072416175794667
473.80788965721683      7      1.3369112993660943
467.5963425076342      2      1.1347258340269681
732.8987625158762      1      0.8263692061788104
310.53302241097754      9      0.4237405351214176
628.6851559377907      3      0.16575050832677962
691.0887987906431      4      0.024920804654023687
262.90565717820226      8      0.3379799298949331
775.8927475464186      10      1.4000064902294738
148.1427616688809      7      0.026272296752586577
420.1966090630077      1      0.6200581196814301
892.7466908387391      11      0.8664981605140172
345.6142794384558      1      1.9806995423184264
758.522431551175      11      1.7413123501982082
153.16707430523817      1      0.8233723250802272
751.1641008681822      11      0.2687336131265847
843.8111609485197      7      0.6646813495940092
0.7641201868734517      5      0.574334334515356
150.2409423296603      4      1.3837452397785408
382.2323512315402      7      1.4794803757768458
796.3557821307547      3      1.8676185578724398
323.2728583013356      11      1.01510680098024
891.3661962863321      2      1.778656701285439
917.524329813358      11      0.4020306651762755
870.2033366730278      2      1.9402185824572158
797.8718226633596      3      0.6392348820481013
571.6086520099294      10      0.03718521466035929
442.280569766938      3      0.019118635701067976
416.5267078180919      9      1.0379843001337004
486.23972583077165      1      1.245342654015108
719.0386022162008      9     ...
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