Spaces:
Sleeping
Sleeping
File size: 5,919 Bytes
6c4d394 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 |
import os
import random
import simpy
import numpy as np
from flask import Flask, render_template, jsonify, request, send_from_directory
app = Flask(__name__, template_folder='templates')
# Configuration
MAX_SIM_TIME = 480 # 8 hours in minutes for analysis
SEED = 42
@app.route('/')
def index():
return render_template('index.html')
@app.errorhandler(404)
def page_not_found(e):
return render_template('index.html'), 404
@app.errorhandler(500)
def internal_server_error(e):
return jsonify(error="Internal Server Error", message=str(e)), 500
@app.route('/api/upload_config', methods=['POST'])
def upload_config():
try:
if 'file' not in request.files:
return jsonify({'error': 'No file part'}), 400
file = request.files['file']
if file.filename == '':
return jsonify({'error': 'No selected file'}), 400
if file:
import json
content = json.load(file)
return jsonify({'message': 'Config uploaded successfully', 'config': content})
except Exception as e:
return jsonify({'error': str(e)}), 500
class CallCenter:
def __init__(self, env, num_employees, service_time_avg, service_time_std):
self.env = env
self.staff = simpy.Resource(env, num_employees)
self.service_time_avg = service_time_avg
self.service_time_std = service_time_std
self.wait_times = []
self.service_times = []
self.utilization_log = []
self.events_trace = [] # For visualization: {'time': t, 'type': '...', 'id': ...}
def support(self, customer):
arrival_time = self.env.now
self.events_trace.append({'time': arrival_time, 'type': 'arrival', 'id': customer})
with self.staff.request() as request:
yield request
wait = self.env.now - arrival_time
self.wait_times.append(wait)
self.events_trace.append({'time': self.env.now, 'type': 'start', 'id': customer, 'wait': wait})
# Service time (Normal distribution, clipped at 0.5 min)
service_duration = max(0.5, random.gauss(self.service_time_avg, self.service_time_std))
yield self.env.timeout(service_duration)
self.service_times.append(service_duration)
self.events_trace.append({'time': self.env.now, 'type': 'finish', 'id': customer})
def customer_generator(env, center, arrival_rate):
"""
arrival_rate: Customers per hour
"""
i = 0
while True:
# Inter-arrival time (Exponential distribution)
yield env.timeout(random.expovariate(arrival_rate / 60.0))
i += 1
env.process(center.support(f'C{i}'))
@app.route('/api/simulate', methods=['POST'])
def simulate():
data = request.json
# Parameters
arrival_rate = float(data.get('arrival_rate', 60)) # Cust/hr
service_time = float(data.get('service_time', 5)) # Avg min
service_std = float(data.get('service_std', 1)) # Std Dev min
num_servers = int(data.get('num_servers', 3))
duration = float(data.get('duration', 60)) # Minutes to simulate
random.seed(SEED)
env = simpy.Environment()
center = CallCenter(env, num_servers, service_time, service_std)
env.process(customer_generator(env, center, arrival_rate))
env.run(until=duration)
# Calculate stats
avg_wait = np.mean(center.wait_times) if center.wait_times else 0
max_wait = np.max(center.wait_times) if center.wait_times else 0
served_count = len(center.service_times)
# Utilization estimate (Total Service Time / (Num Servers * Duration))
total_service = sum(center.service_times)
utilization = (total_service / (num_servers * duration)) * 100 if num_servers > 0 else 0
return jsonify({
'metrics': {
'avg_wait': round(avg_wait, 2),
'max_wait': round(max_wait, 2),
'served': served_count,
'utilization': round(utilization, 2)
},
'trace': center.events_trace
})
@app.route('/api/optimize', methods=['POST'])
def optimize():
data = request.json
arrival_rate = float(data.get('arrival_rate', 60))
service_time = float(data.get('service_time', 5))
service_std = float(data.get('service_std', 1))
cost_per_server_hr = float(data.get('cost_server', 20)) # $20/hr
cost_per_wait_hr = float(data.get('cost_wait', 50)) # $50/hr (Value of customer time/frustration)
results = []
# Test 1 to 15 servers
for n in range(1, 16):
random.seed(SEED) # Reset seed for fair comparison
env = simpy.Environment()
center = CallCenter(env, n, service_time, service_std)
env.process(customer_generator(env, center, arrival_rate))
env.run(until=480) # 8 hours
avg_wait_min = np.mean(center.wait_times) if center.wait_times else 0
total_wait_hours = sum(center.wait_times) / 60.0
# Total Cost = (Server Cost * 8h) + (Total Wait Hours * Wait Cost)
server_cost = n * cost_per_server_hr * 8
wait_cost = total_wait_hours * cost_per_wait_hr
total_cost = server_cost + wait_cost
utilization = (sum(center.service_times) / (n * 480)) * 100
results.append({
'servers': n,
'total_cost': round(total_cost, 2),
'server_cost': round(server_cost, 2),
'wait_cost': round(wait_cost, 2),
'avg_wait': round(avg_wait_min, 2),
'utilization': round(utilization, 1)
})
# Optimization: if cost starts increasing significantly and wait is low, we can stop,
# but let's run all 15 for the chart.
return jsonify({'results': results})
if __name__ == '__main__':
app.run(host='0.0.0.0', port=7860, debug=True)
|