drl-supply-chain-sq-sim.py

class SQPolicy(object):
    def __init__(self, factory_safety_stock, 
                 factory_reorder_amount, safety_stock, reorder_amount):
        self.factory_safety_stock = factory_safety_stock
        self.factory_reorder_amount = factory_reorder_amount
        self.safety_stock = safety_stock
        self.reorder_amount = reorder_amount

    def select_action(self, state):
        action = Action(state.warehouse_num)
        for w in range(state.warehouse_num):
            if state.warehouse_stock[w] < self.safety_stock[w]:
                action.shippings_to_warehouses[w] = self.reorder_amount[w]
    
        if state.factory_stock - np.sum(action.shippings_to_warehouses) < self.factory_safety_stock: 
            action.production_level = self.factory_reorder_amount
        else: 
            action.production_level = 0
        return action
    
def simulate_episode(env, policy):
    state = env.initial_state()
    transitions = []
    for t in range(env.T):
        action = policy.select_action(state)
        state, reward, _ = env.step(state, action)
        transitions.append([state, action, reward])
    return transitions

# Basic policy evaluation process 
def simulate(env, policy, num_episodes):
    returns_trace = []
    for episode in range(num_episodes):
        env.reset()
        returns_trace.append( sum(np.array(simulate_episode(env, policy)).T[2]) )
    return returns_trace