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Abstract
Multi-level programming, techniques are developed to solve planning problems with multiple decision makers in a decentralized hierarchical organization.
There are coming features of multi-level organization: interactive decision-making of dexist within a predominantly interarchical structure execution of decisions is sequential, from top be bottom levels, each unit independently maximizes its own benefits, but is affected by the actions of other units through bxternalities; the external effect on a decision maker’s problem can be reflected in both objective function and the set of feasible decisions.
The basic concepts of multi-level programming techniques are as follows: an upper-level decision maker sets his or her goal and/or decisions and then asks each subordinate level of the organization for their optima which are calculated in isolation; the lower-level decision makers decisions are then submitted and modified by the upper-level decision maker with consideration of the overall benefit for the organization; and the process is continued until a satisfactory solution is reached.
This decision-making process is extremely practical to such decentralized systems as agriculture, government policy, economic systems, transportation, network designs and is especially suitable for conflict resolution.
This thesis consists of six chapters, the title of each and a summary of its contents are given below.
Chapter 1 presents a survey on methods and theory of multi- level programming problems in one place to provide a guide for users and reserchers.
Chapter 2 presents three-planner multi-objective making model and an interactive algorithm The algorithm simplifies decision for solving such mode multi-objective a three-level non-linear decision-making problem by transforming it into separate multi- objective decision-making problems with hierarchical structure, and solving it by using &-constraint method to avoid the difficulty associated with non-convex mathematical programming.
In addition, the satisfactoriness concept as the first-level and the second-level decision-maker’s preference are put forward. Also, the illustrative numerical example is given to demonstrate the obtained results.
Chapter 3 presents a study on multi-level non-linear multi-objective decision-making problem under fuzziness in two cases. First case presents a bi-level non-linear multi-objective decision-making problem under fuzziness.
Second case extends a three-level non-linear multi-objective decision-making problem under fuzziness.a three-planner multi- objective decision-making model and solution method for solving this problem is presented. This method uses the concepts of tolerance membership function and multi-objective optimization at each level to develop a fuzzy Max-Min decision model for generating a non-inferior (satisfactory) solution for three-level non- linear multi-objective decision-making problem. Also, two illustrative numerical examples are given to demonstrate the obtained results.
Chapter 4 has applied a hybrid approach for modeling decentralized multi-level systems, which allows all decision- makers to have different objective functions.
The hybrid approach for multi-level non-linear multi- objective decision-making problem is combine the interactive approach and the fuzzy approach for solving the multi-leveactive linear multi-objective decision-making problem
Chapter 5 has applied two different approaches of bi-level programming technique, lecu solve a real problem, the supply demand interaction in electronic commerce (EC) taking into account the non linear model to such problem , to make a comparative study between the two approaches. An illustrative numerical example, of the application problem, is given to demonstrate the obtained results.
Chapter 6, contains the conclusions and some points for future research in the field of multi-level non-linear programming problems will be presented.