51 lines
1.3 KiB
Python
51 lines
1.3 KiB
Python
import numpy as np
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from typing import Optional
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from enum import Enum
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class State(Enum):
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SOLVED = 0
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UNSOLVED = 1
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UNAPPLICABLE = 2
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class Result:
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solved: State
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objective_function_value: Optional[np.float64]
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solution: Optional[np.array[np.float64]]
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def __init__(self,
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solved: State,
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objective_function_value: Optional[np.array[np.float64]] = None,
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solution: np.float64 = None):
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self.solved = solved
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self.objective_function_value = objective_function_value
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self.solution = solution
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def interior_point(
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C: np.array[np.float64],
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A: np.array[np.float64],
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x_0: np.array[np.float64],
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b: np.array[np.float64],
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eps: np.float64 = 0.01,
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alpha: np.float64 = 0.5,
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maximizing: bool = True) -> Result:
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if (not np.all(np.dot(A, x_0) >= b) or np.any(x_0 == 0)):
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return Result(State.UNAPPLICABLE)
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if (not maximizing):
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C = -C
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x = x_0
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solved = False
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while not solved:
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# TODO Algorithm steps (refer to numpy.linalg for matrix stuff)
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pass
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# return value (include check for minimization)
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return Result(State.SOLVED, ...)
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# TODO 5 tests (from assignment 1) and comparison with simplex and alpha = 0.9
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def TEST_CASE_GENERAL():
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pass
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