استعمال الخوارزمية المهجنة انجل في حل نماذج حقيبة الظهر في الشركة العامة للسكك الحديد == Using Hybrid Algorithm Angel To Solving The Models of Knapsack P In The General Company For Railways
Author name:
ايمان حسن هادي الزبيدي
Supervisor name:
عدنان شمخي جابر
General topic:
Administration and Economics
Specific topic:
Operations Research
Degree:
Master
University:
University of Baghdad - Faculty Of Administration And Economics - Department Of Statistics
Language:
Arabic
University location:
Baghdad
First pages:
07T3459 - p.pdf
Abstract:
تعد مسالة حقيبة الظهر (Knapsack problem) من مسائل الامثلية المركبة (COP) (مسائل تمتلك كما هائلا من الحلول البديله) ,ولما لها من اهمية من جميع الجوانب فيما يتعلق بخاصية الاستغلال الامثل للعناصر المحمولة بها ,اذ تم في هذا البحث دراسة مسالة حقيبة الظهر من | The problem of Knapsack (Knapsack problem) of the fitness problem composite (COP) (problem possess a tremendous amount of alternative solutions), and because of their importance in all aspects with regard to feature the best use of phones out of the elements, as it has been in this research study the issue of Knapsack in terms of models and methods and their applications to solve their importance and their uses in the broad economic aspects of being a help to maximize returns through optimal choice for portable goods that achieve the highest possible profit. As the issue and Knapsack (KP) belong to the complexity of the problem of the type (NP - - Complete) and does not possess the polynomial time algorithm was used meta heuristic algorithm solution because these algorithms possess speed of implementation and also the ability to access good solutions in a reasonable time, as was the use of hybrid algorithm (ANGEL) consisting of three meta heuristic algorithms to resolve the matter (optimize ant colonies algorithm (ACO) local search procedure (LS) and the genetic algorithm (GA)). The first stage is the use of ant colonies optimization in building a set of solutions and then improves them through local search and then using genetic algorithm considering society resulting from the previous stage is the first community of genetic algorithm. Hybrid algorithm proved (ANGEL) speed and proficiency in access to good solutions when compared with Simulated Annealing algorithm (Simulated Annealing) genetic algorithm (Genetic Algorithm) after solving (10) problems randomly generated test different sizes (50 - 1000) and the average earnings when using hybrid algorithm (ANGEL) (23878.6) while Simulated Annealing algorithm (Simulated Annealing) (1603.257) genetic algorithm (Genetic Algorithm) (15555.64), The average time spent for hybrid algorithm (ANGEL) (726.908) seconds, while the time it takes to both algorithm (Simulated Annealing algorithm and genetic algorithm) respectively is (21953.25) (39432) again, and the results were also compared with a hybrid algorithm of conventional roads branching algorithm and seized (Branch and Bound) in terms of the time it takes to reach an optimal solution, where the average time year hybrid algorithm (ANGEL) (726.908) seconds while branching and selection algorithm (23582.98) again and finally use issue in maximizing the proceeds of public company To Iraqi railways amounted to gross profit (31,193,349).
