Given the following input instance for the 0/1 Knapsack problem. Show how the algorithm given in the class works on this input instance. Complete the whole (M+1)x(n+1) table, and give the answer for the optimal solution, where M is the capacity of the knapsack and n is the number of objects. Object 1 Object 2 Object 3 Object 5 |Object 6 Profit pi 3 3 5 1 4 Weight w; | 2 4 5 3 М-10

Given the following input instance for the 0/1 Knapsack problem. Show how the algorithm given in the class works on this input instance. Complete the whole (M+1)x(n+1) table, and give the answer for the optimal solution, where M is the capacity of the knapsack and n is the number of objects. Object 1 Object 2 Object 3 Object 5 |Object 6 Profit pi 3 3 5 1 4 Weight w; | 2 4 5 3 М-10

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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This assignment uses several heuristic search techniques to find possibly optimal truth assignments for variables in the given Boolean formulas (see the bottom of the assignment). The formulas are in conjunctive normal form (ANDs of ORs). The fitness of an assignment is the number of clauses (ORs) that the assignment satisfies. If there are c clauses, then the highest fitness is bounded by c. However, if the formula is not satisfiable, then you cannot simultaneously make all c clauses true. You will use three of the following seven techniques: DPLL Resolution Genetic algorithms Local search Simulated annealing GSAT WalkSAT You must choose at least one complete algorithm to implement - DPLL or Resolution.
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