Chapter 2 Related work 2.1 Introduction: Multiple constraint satisfaction problems (MCSP) is a problem in which a set of values must meet a number of constraints. it has been widely used in AI to solve a wide range of problems. In this thesis we use MCSP to solve the load balancing proble. Therefore, we first review the different algorithms in MCSP and the Dynamic MCSP then we review the load balancing problem. 2.2 Constraint Satisfaction Problem: CSPs are mathematical problems which are defined as a set of values that must meet a number of constraints or state restrictions. The problem is to search for a set of values for the features (or variables) so that the values satisfy some conditions (or constraints). A CSPs consists of a set of variables; For each variable, a limited range of possible values (domain); and a set of constraints that restrict the values of variables that can be taken at one time. CSPs solution is to assign a value for each variable, in such way that all assignment satisfy all restrictions or constraints. Since the possible values of the variables are limited, thus this kind of problem is combinatorial in nature and NP-complete. Formally, A CSP is defined as a triplet (X , D, C) where …show more content…
there is no consistent partial solution. it revises the variables by using hill-climbing (Makoto and Katsutoshi, 1996) search untill it reaches the ideal solution. The min-conflicts heuristic (Minton, et al., 1992) is a local search for solving CSPs. This heuristic chooses randomly variable in the scope of the restriction violated, and assigns it to a value in its domain that reduces the number of restrictions violated. If there is more than one value, it randomly selects among them. but the main weak point of the min-conflicts heuristic is that the possibility of being caught in a local, non solution minimum, which leads to restart the algorithm from a new initial
How did Steve Heller define the problem describe in this case? How did Pam LaBlanc define the problem? How did the problem definition affect the way these two people initially solved the problem?
Problem solving is the process of following a series of steps to obtain the solution
Well-defined problems are those that have clear, defined goals and can be met in a formal and set number of steps. An example of a well-defined problem would be a math equation such as 2(x) + 4 = 10. In order to understand how to solve said problem first we ought to know the meaning of the mathematical symbols and numbers, and define the goal, which in this case is to figure out the value of “x”. We have to know that “( )”; aside from their typical use in writing, tell us to enclose and multiply whatever numbers or symbols are between them with the numbers or symbols outside of them; as well as recognize that “+” means addition or more. We must also infer that since the whole equation has to equal to 10 after being multiplied by...
The past is often said to be the best predictor of the future. In planning and forecasting for future labor needs, based on gaps in employment levels due to advancements, demotions, or exiting employees within a company, a review of a Markov Analysis chart can reflect areas of opportunity for the organization based on past employment movements (Dartmouth, n.d.). The Doortodoor Sports Equipment Company is unique in their industry, being in the only company to sell door to door. However, this tactic as well as other HR practices could be examined to determine if changes employed increase retention or improve internal promotions. A review of the Markov Analysis for the Doortoodoor Sports Equipment Company will now be considered.
A description of the nature of the problem, including facts relating to such problem; and
Cormen T. H, Leiserson C. E., Rivest R. L. and Stein C. [1990] (2001). “Introduction to Algorithms”, 2nd edition, MIT Press and McGraw-Hill, ISBN 0-262-03293-7, pp. 27–37. Section 2.3: Designing algorithms..
Problem solving is defined as cognitive processing directed toward achieving a goal, including problem representation.
CSR is a concept where company involves in social and environmental in their business operations. This is done to achieve a balance of economic, environmental and social obligations.in simple terms giving a hand for those who are not capable of achieving with their objectives and attending to them so that they could make those objectives a reality. This could improve organizations cooperate image which would also leads to attain a high market share.
CSR can relate to social, environment and profit goals. CSR enhances awareness of human, environmental and social issues and places pressure on organizations to adopt procedures and policies that are good for stakeholders wellbeing. Scholars have different definitions for CSR as seen below:
The set-theoretic representation is one of the ways to represent a planning problem. Given a finite set $L$ of propositions, we can describe the environment as following:
DSS is a system which aids management in some stages in the decision process in situation where some aspects of the process are not well structured or well defined. Decision support software can assists the decision maker in each of the steps in Figure 17-1. It can signal the need for a decision through an exception report. Software can be used to accumulate and organize the data so that managment can be better understand the nature of the problem. It can be used ...
There are now several concepts of CSR and its definition, along with the meaning across corporations. In my opinion, and according with our textbook in page 11. CSR is about a particular set of business and strategies that deal with social issues. In addition, we can clearly perceive that CSRs application along corporations has increase in the past decade due to the several local, and international regulations in order to enforce business to act responsible.
it is a solution to a given problem. Students must be required to think mathematically for
Generates only a single point solution for each iteration, a sequence of those converging to the optimal solution.
The range of task environments that can be characterized by well - defined problems is vast. We can distinguish between so - called, toy problems, which are intended to illustrate or exercise various problem - solving methods, and so - called real - world problems, which tend to be more difficult and whose solutions people actually care about. In this section, we will give examples of both. By nature, toy problems can be given a concise, exact descri ption. This means that they can be easily used by different researchers to compare the performance of algorithms. Real - world problems, on the other hand, tend not to have a single agreed - upon description, but we will attempt to give the general flavor of t heir formulations.