(1999) proposed an algorithm combining dynamic programming with tight bounds and core concept. Pisinger (2005) presented some types of the hard KP instances ...
"Solution of “Hard” Knapsack Instances Using Quantum Inspired Evolutionary Algorithm," International Journal of Applied Evolutionary Computation (IJAEC), IGI ...
Solution of “Hard” Knapsack Instances Using Quantum Inspired Evolutionary Algorithm. Maximize: Subject to: j n. j j j n. j j. p x. w x. C. = = ∑. ∑. ≤. 1. 1.
Request PDF | Solution of “Hard” Knapsack Instances Using Quantum Inspired Evolutionary Algorithm | Knapsack Problem (KP) is a popular combinatorial ...
The problem is known to be NP-hard and arises in several domains including finance, VLSI design and location problems. Greedy heuristics and Genetic Algorithms ...
Jan 1, 2014 · Solution of "Hard" Knapsack Instances Using Quantum Inspired Evolutionary Algorithm. Authors: C. Patvardhan. C. Patvardhan. Department of ...
(PDF) Solution of “Hard” Knapsack Instances Using Quantum ...
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Solution of “Hard” Knapsack Instances Using Quantum Inspired Evolutionary Algorithm ... Knapsack Problem (KP) is a popular combinatorial optimization problem ...
The standard knapsack problem (SKP) is NP-hard in the weak sense, meaning that it can be solved in pseudo-polynomial time through dynamic programming. The SKPs.
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QKP is NP Hard in stronger sense i.e. no pseudo-polynomial time algorithm is known to exist which can solve QKP instances. QKP has been studied intensively due ...