This paper presents the heuristic algorithm Maximizing Value per Resources Consumption (MVRC) that solves the Multi-Choice Multi-Constraint Knapsack Problem, a variant of the known NP-hard optimization problem called Knapsack problem. Starting with an initial solution, the MVRC performs iterative improvements through exchanging the already picked items in order to conclude to the optimal solution. Following a three step procedure, it tries to pick the items with the maximum Value per Aggregate Resources Consumption. The proposed algorithm has been evaluated in terms of the quality of the final solution and its run-time performance.
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