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Tick the correct statement :

ADishonestly receiving stolen computer resource or communication device is punishable offence in Indian Law

BDishonestly receiving stolen computer resource or communication device is not punishable offence in Indian Law

CDishonestly receiving stolen computer resource is not an offence in Indian Law

DAll above are False

Answer:

A. Dishonestly receiving stolen computer resource or communication device is punishable offence in Indian Law

Read Explanation:

Overview of Linear Programming and Operations Research

  • Linear Programming (LP) is a mathematical technique used to determine the best outcome in a model whose requirements are represented by linear relationships.
  • The objective function and the constraints must be linear equations or inequalities.
  • The feasible region is the set of all possible points that satisfy all constraints. If a solution exists, the optimal solution always lies at a corner point (vertex) of the feasible region.

Key Concepts for Competitive Exams

  • Decision Variables: The unknown quantities to be determined (e.g., how many units to produce).
  • Objective Function: A mathematical expression that needs to be either maximized (like profit) or minimized (like cost).
  • Constraints: Restrictions on resources such as labor, material, time, or budget, usually represented as Ax ≤ B or Ax ≥ B.
  • Non-negativity Constraint: Decision variables must typically be greater than or equal to zero (xi ≥ 0), as negative production is physically impossible in most scenarios.

Assumptions in Linear Programming

  • Proportionality: The contribution of each decision variable to the objective function and constraints is directly proportional to its value.
  • Additivity: The total contribution of all variables is the sum of individual contributions.
  • Divisibility: Decision variables can take on any real value (fractions/decimals are allowed). If integer values are required, it becomes an Integer Programming problem.
  • Certainty: The parameters (coefficients) of the model are assumed to be known with absolute certainty.

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