Archives: Solution Manual

Data Table Calculations set to Manual. Press F9 to recalculate. 25 Dry 276 276 $270.00 25 $7,711.25 26 Dry 315 300 $300.00 26 $7,395.00 27 Dry 284 284 $280.00 27 $7,726.25 28 Dry 292 292 $290.00 28 $7,688.75 29 Dry […]

Data Table Calculations set to Manual. Press F9 to recalculate. 25 Minor $74 27 $23,841 26 Minor $106 28 $15,863 27 Minor $102 29 $16,369 28 Minor $115 30 $15,241 29 Minor $110 31 $19,963 30 Minor $137 32 $20,454 […]

P10-33 Data Table Calculations set to Manual. Press F9 to recalculate. Month Begin Inv Units Rec Avail Inv Demand Demand Filled End Inv Stock out End Inv + Order Place order? Lead time Arrive on day Inv cost Stockout cost […]

Data Table Calculations set to Manual. Press F9 to recalculate. Custo- mer # Time between arrivals Arrival time Start service Service time End service Wait time Arrive within 1 hour? RN intvl LL Time Proba- bility Run Wait time 0 […]

P10-31 Calculations set to Manual. Press F9 to recalculate. Pati- ent Room 1 Room 2 Room 3 Room 4 Room 5 Room 6 Roo m 7 Roo m 8 Room 9 Room 10 Room 11 Room 12 Room 13 Room […]

Problem 10-30 Data Table (Calculations set to Manual. Press F9 to recalculate). Maximum res accepted = 9 RN intvl LL Value Probability Run Profit Demand = 7 1 $174 Actual res accepted = 7 2$24 Number no shows = 0 […]

Data Table Calculations set to Manual. Press F9 to recalculate. Day Begin Inv Units Rec Avail Inv Dem- and Demand Filled End Inv Stockout End Inv + Order Place order? Lead time Arrive on day Inv cost Stock out cost […]

Data Table Calculations set to Manual. Press F9 to recalculate. Day Begin Inv Units Rec Avail Inv Dem- and Dem- and filled End Inv Stock out End Inv + Order Place order? Lead time Arrive on day Inv cost Stockout […]

Data Table Calculations set to Manual. Press F9 to recalculate. Day Begin Inv Units Rec Avail Inv Dem- and Dem- and filled End Inv Stock out End Inv + Order Place order? Lead time Arrive on day Inv cost Stockout […]

Data Table (Calculations set to Manual. Press F9 to recalculate). Day Begin Inv Units Rec Avail Inv Dem and Demand Filled End Inv Stock out End Inv + Order Place order? Lead time Arrive on day Inv cost Stockout cost […]

Data Table (Calculations set to Manual. Press F9 to recalculate). Day Begin Inv Units Rec Avail Inv Dem and Demand Filled End Inv Stock out End Inv + Order Place order? Lead time Arrive on day Inv cost Stockout cost […]

Data Table Calculations set to Manual. Press F9 to recalculate. Week Begin Inv Units Rec Avail Inv Dem- and Demand Filled End Inv Stockout End Inv + Order Place order? Lead time Arrive on week Inv cost Stockout cost Order […]

P10-23 Data Table Calculations set to Manual. Press F9 to recalculate. Patient Sched appt time Actual arrive Sched time needed Act time needed Start service Finish service Run Finish service Ada 0 0 20 16 016 Minutes Probability RN intvl […]

P10-22 Data Table Calculations set to Manual. Press F9 to recalculate. Stude nt Sched appt time Actual arrive Sched time needed Act time needed Start service Finish service Run Finish service 1 0 -10 20 20 020 Minutes Probability RN […]

P10-21 Data Table Calculations set to Manual. Press F9 to recalculate. Run Total time Cost/hr Total time Cost/hr # Time (Hrs) # Time (Hrs) Hours Probability RN intvl LL 1800 $14.50 2,470 $10.69 130 1130 10 0.05 0 2 750 […]

Data Table (Calculations set to Manual. Press F9 to recalculate). Day Demand Revenue Cost Profit Run Profit 129 $435.00 $120.00 $315.00 Mean = 30 1 $7,515.00 43 $7,560.00 44 $7,290.00 45 $7,395.00 46 $7,185.00 47 $7,275.00 48 $7,320.00 49 $7,725.00 […]

Data Table Calculations set to Manual. Press F9 to recalculate. Day Demand Today Revenue Cost Next-Day Revenue Profit Demand Probability RN intvl LL Run Profit 42 $32,625.00 43 $33,750.00 44 $27,375.00 45 $30,000.00 46 $31,875.00 47 $31,500.00 48 $27,375.00 49 […]

29 100 $300.0 $200.0 $100.0 29 $4,356 30 175 $300.0 $200.0 $100.0 30 $4,975 31 125 $300.0 $200.0 $100.0 31 $4,638 32 75 $243.8 $200.0 $43.8 32 $4,525 33 150 $300.0 $200.0 $100.0 33 $4,919 34 125 $300.0 $200.0 $100.0 […]

P10-17 Data Table Calculations set to Manual. Press F9 to recalculate. Month Begin Bal Income Expense End Bal Run End bal P(neg bal) 1 $1,500 $950 $1,000 $1,450 Income Probability RN intvl LL 1$400 0.0000 2 $1,450 $900 $800 $1,550 […]

(Calculations set to Manual. Press F9 to recalculate). Month Demand 125 Demand Probability RN intvl LL 230 10 0.02 0.00 325 15 0.07 0.02 33 35 34 25 35 35 36 35 37 25 38 15 39 25 40 40 […]

P10-14 Month Failures 1 4 Lwr Lmt Failures Probability 2 3 0 0 0.10 13 5 Expected failures/month 2.48 18 3 19 3 20 3 21 2 22 2 23 1 24 1 25 1 26 3 27 4 33 […]

Data Table Calculations set to Manual. Press F9 to recalculate. Week Demand Profit Run Avg profit Prob >= 200 20 42 $2,100.00 20 $1,700.96 15.38% 21 30 $1,500.00 21 $1,704.81 3.85% 22 38 $1,900.00 22 $1,768.27 17.31% 23 31 $1,550.00 […]

techniques. Problems that require quick answers that cannot wait for a simulation model to be built are a second category. probabilistic) elements through random sampling. Monte Carlo steps: (1) set up probability distribution(s), (2) set up cumulative probabilities, (3) establish […]

Data Table Calculations set to Manual. Press F9 to recalculate. Production per day (tons) 100 Number of failures 1 Run Cost Days lost Profit per ton $12 RN intvl LL Failures Probability 1 $28,800 24 Average production days lost 26.5 […]

CHAPTER 10 SIMULATION MODELING Internet Case Study: Buffalo Alkali and Plastics To analyze this problem, we develop two simulation models. The first model, which is shown in file Ch10 Internet Case Buffalo Alkali.XLS, sheet Current, assumes that repair times follow […]

Biales Data Table Calculations set to Manual. Press F9 to recalculate. Trip No. of barrels Rev per barrel Run Profit 143 60 RN intvl LL Barrels Probability 1 -6220 243 60 0.00 28 0.12 2 -3970 748 60 7 -9330 […]

CHAPTER 10 SIMULATION MODELING Internet Case Study: Biales Waste Disposal, GmbH Each trip out of Italy costs DM 900 for shipment and another DM 120 for loading and unloading. If there are 25 trips, the annual cost to operate the […]

Data Table Calculations set to Manual. Press F9 to recalculate. Custo- mer # Time between calls Call arrival time Call start service Service time Call end service Wait time Agent idle time RN interval lower limit Time Proba- bility Run […]

Abjar Transport Company Data Table Calculations set to Manual. Press F9 to recalculate simulation values. 29 820 30 820 31 514 32 822 33 10 26 34 923 35 821 36 719 37 821 38 11 29 39 821 40 […]

(b) The probability of getting a 5-inch nail is = 0.19. (c) The probability of getting a nail 3 inches or shorter is the probability of getting a nail 1 inch, 2 inches, or 3 inches in length (the events […]

exclusive events can be seen in flipping a coin. The outcome of any one trial can either be a head or a tail. Thus, the events of getting a head and a tail are mutually exclusive because only one of […]

Problem 9-39 Queuing Model M/M/s with a finite population Input Data Operating Characteristics Arrival rate per customer (l) 0.9090909 Average server utilization (r)0.7190 Probabilities 8.143153 Number of Units Probability Cumulative Probability Number waiting Arrival rate(n) Term 1 Sum term 1 […]

Problem 9-38 Queuing Model M/G/1 (General Service Times) Input Data Operating Characteristics Arrival rate (l)8Average server utilization (r)0.8000 Service rate (m)10 Average number of customers in the queue (Lq)1.7778 Standard deviation (s)0.0333 Average number of customers in the system (L) […]

1 2 3 4 17 18 19 20 21 22 23 24 25 Desired waiting time of 6 seconds, or 0.1 minutes Probabilities Desired queue length of 8 cummuters Number of Units Probability Cumulative Probability 0 0.0502 0.0502 1 0.1406 […]

Problem 9-36 Queuing Model M/M/s with a finite population Input Data Operating Characteristics Arrival rate per customer (l) 0.03 Average server utilization (r)0.6899 Service rate (m)0.2 Average number of customers in the queue (Lq)0.7105 Probabilities 3.225126 Number of Units Probability […]

Problem 9-35 Queuing Model M/M/s with a finite population Input Data Operating Characteristics Arrival rate per customer (l) 0.5 Average server utilization (r)0.6918 Service rate (m)4Average number of customers in the queue (Lq)0.7735 Probabilities 3.245018 Number of Units Probability Cumulative […]

Problem 9-34 Queuing Model M/M/s with a finite population Input Data Operating Characteristics Arrival rate per customer (l) 0.7058824 Average server utilization (r)0.6635 Probabilities 2.971843 Number of Units Probability Cumulative Probability Number waiting Arrival rate(n) Term 1 Sum term 1 […]

Problem 9-33 Queuing Model M/M/s with a finite population Input Data Operating Characteristics Arrival rate per customer (l) 0.1 Average server utilization (r)0.5155 Service rate (m)1Average number of customers in the queue (Lq)0.3297 Probabilities 2.06392 Number of Units Probability Cumulative […]

Queuing Model M/G/1 (General Service Times) Input Data Operating Characteristics Arrival rate (l)0.9 Average server utilization (r)0.9000 Problme 9-32 (m = 1) Service rate (m)1Average number of customers in the queue (Lq)5.0625 Standard deviation (s)0.5000 Average number of customers in […]

Problem 9-31 Queuing Model M/G/1 (General Service Times) Input Data Operating Characteristics Arrival rate (l)0.125 Average server utilization (r)0.6250 Service rate (m)0.2 Average number of customers in the queue (Lq)0.5417 Standard deviation (s)1.0000 Average number of customers in the system […]

Queuing Model M/D/1 (Constant Service Times) Input Data Operating Characteristics Arrival rate (l)4Average server utilization (r)0.6667 Problem 9-30 Service rate (m)6Average number of customers in the queue (Lq)0.6667 Average number of customers in the system (L) 1.3333 Average waiting time […]

Problem 9-29 Queuing Model M/G/1 (General Service Times) Input Data Operating Characteristics Arrival rate (l)1Average server utilization (r)0.3797 Service rate (m)2.633836 Average number of customers in the queue (Lq)0.1666 Standard deviation (s)0.2500 Average number of customers in the system (L) […]

Problem 9-28 Queuing Model M/G/1 (General Service Times) Input Data Operating Characteristics Arrival rate (l)1Average server utilization (r)0.5000 Service rate (m)2Average number of customers in the queue (Lq)0.3125 Standard deviation (s)0.2500 Average number of customers in the system (L) 0.8125 […]

1 2 3 4 5 6 7 8 9 17 18 32 33 34 35 36 37 38 39 40 12 0.0126 0.9732 13 0.0086 0.9818 14 0.0058 0.9876 15 0.0040 0.9916 16 0.0027 0.9943 17 0.0018 0.9961 18 0.0012 […]

1 2 3 4 5 6 7 8 9 15 16 17 18 32 33 34 35 36 37 38 39 12 0.0000 1.0000 13 0.0000 1.0000 14 0.0000 1.0000 15 0.0000 1.0000 16 0.0000 1.0000 17 0.0000 1.0000 18 […]

Problem 9-25 Queuing Model M/G/1 (General Service Times) Input Data Operating Characteristics Arrival rate (l)10 Average server utilization (r)0.8333 Service rate (m)12 Average number of customers in the queue (Lq)2.2708 Standard deviation (s)0.0250 Average number of customers in the system […]

1 2 3 4 5 21 22 23 24 25 26 27 28 29 30 1 0.2479 0.7022 2 0.1353 0.8375 3 0.0738 0.9113 4 0.0403 0.9516 5 0.0220 0.9736 6 0.0120 0.9856 7 0.0065 0.9921 8 0.0036 0.9957 9 […]

1 2 3 4 5 14 15 16 17 18 19 20 21 22 23 24 25 26 27 Number of Units Probability Cumulative Probability 0 0.4118 0.4118 1 0.3431 0.7549 2 0.1430 0.8979 3 0.0596 0.9574 4 0.0248 0.9823 […]

1 2 3 4 5 6 7 8 17 18 20 00.1667 0.1667 22 20.1157 0.4213 24 40.0804 0.5981 26 60.0558 0.7209 28 80.0388 0.8062 33 34 35 36 37 38 39 40 13 0.0156 0.9221 14 0.0130 0.9351 15 […]

1 2 3 4 5 6 7 8 9 17 18 22 20.1764 0.3140 24 40.1633 0.6733 26 60.0726 0.8548 27 28 70.0484 0.9032 80.0323 0.9355 33 34 35 36 37 38 39 40 13 0.0042 0.9915 14 0.0028 0.9943 […]