In basic words, in an optimization issue, you need to either minimize or maximize the result (the objective or cost function). Of course, you can't generally optimize a situation without some particular constraints. For example, how does a worldwide petroleum refiner choose where to purchase raw petroleum, where it should be processed, what product should be produced by using it, where to
Hybrid optimization algorithm for solving non-convex NLP/MINLP problems with constraints 1.1 BASIC CONCEPTS (a) LINEAR PROGRAMMING: Linear programming (LP; also called linear optimization) is a method to obtain the best result (such as maximum profit or lowest cost) whose requirements and constraints are depicted by linear relationships, in a mathematical model. Linear programming is a special sub-case of mathematical programming (mathematical optimization). On a more clear note, linear programming is a method for the optimization of a linear objective function, subject to linear equality and linear inequality constraints. Its best domain of region is a convex polytope, which is a set of intersection of finitely many half spaces, each of which is constituted of a linear inequality. Its chief function is a real-valued affine (linear) function defined on this polyhedron.
Mathematical Programming is an exact approach to combinatorial Optimization Programming. Traditional methods from linear programming, integer programming, GP networks have been employed to solve the NRP. Decision Problem: In situations where there are a large number of constraints to be dealt with, it can be more appropriate to model the NRP as a constraint satisfaction Problem (CSP). Feasible solutions to the CSP are the assignments of values to variables satisfying all constraints. Decision problems usually solve by Heuristics or
McWhinney theory of problem-solving has identified a series of different approaches to solving complex problems in the organisation based on how the company views the realities, problem-solving and change management process. The Modes of change or approaches are formed by combining the four realities or worldviews into six distinct combinations. The different modes of change described in the McWhinney problem-solving model include Analytic, Assertive, Influential, Evaluative, Inventive and Emergent. As per McWhinney model, Pairing of realities grouped in the Unitary and Sensory quadrants result in Analytic
Working (1934) mentioned that stock return behaved like a number in the lottery. Several studies in the 1950s documented features of stock market that resembles those of an efficient market. Friedman (1953) found that efficient market can exit in a situation where trading strategies of investors are correlated, due to the existence of arbitrage. Kendall (1953), analyzing 22 weekly price series, found that stock prices movement at a close interval moved randomly. He mentioned that prices behaved like wondering series and showed very low serial correlation.
Optimization Algorithm The Optimization Algorithm is a step-by-step procedure to solve a problem and get the exact value or can say optimal value of that problem. There are 2 Optimization Algorithms : • Genetic Algorithm (G. A.) • Particle Swarm Optimization Algorithm (P. S. O.)
The nursing shortage increases opportunity, but with opportunity, comes with some consequences. Job dissatisfaction can result in exhaustion, and injury if nurses work long hours in their stressful working conditions. Nurses would be more prone to making mistakes and errors in these environments. The patients can suffer from low quality care. This shows how stressed nurses are from being overworked.
Nyathi and Jooste (2008) has studied that the absenteeism of nurses has led the healthcare industry to the increase in shortage of staff. The managers of nurses are expected to experience the challenges in modifying their schedules and reallocating the tasks and responsibilities of the ones being absent from the work to the ones present for ensuring the consistent patient care within the unit. It is also highlighted that the allocation of nurse stands in for the absent colleague is possibly not familiar with the required tasks to be performed. On the other hand, Wang and Gupta (2014) assessed that there are some hospitals creating the pool of nurses, who are possibly assigned to different units on the basis of the short term variations as
Linear programming optimization used matrices and necessary to businesses if they want to calculate maximum revenue over a set of limits. It’s used for hydroelectric power plants for a restricted diet caloric intake optimization. Matrices are fundamental to calculus which is very important to many industrial businesses. Example 1) BCG Matrix: Coca Cola & Pepsi Cola. The matrix are misrepresenting of some cases.