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Register a new userModified Hybrid Algorithm To Contribute in Solving The Multi- Objective Vehicle Routing Problem With Time windows Based On Pareto Optimization
خوارزمية بحث هجينة معدلة للمساهمة في حل مسألة توجيه المركبة مع نوافذ زمنية متعددة الأهداف على أساس أمثلية باريتو
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Aِl-Baath University ورقة بحثية
Publication date
2017
fields
Mathematics
and research's language is
العربية
Created by
Shamra Editor
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ندرس في هذا البحث إمكانية المساهمة في حل مسألة توجيه المركبة مع نوافذ زمنية متعددة الأهداف ، و هي واحدة من مشاكل الأمثلية من النوع NP-hard, حيث أخذت كثيرًا من اهتمام الباحثين في الوقت الحاضر بسبب تطبيقاتها المتعددة ذات الطابع اليومي . و سنقدم أيضاً خوارزمية تدعى بالهجينة تعتمد على مبدأ التكامل بين خوارزمية مستعمرة النمل متعددة الأهداف و خوارزمية البحث المحظور ، و المستندة على أمثلية باريتو و مقارنة الحل الناتج عن هذا النهج الهجين المطور و المستند على أمثلية باريتو مع نتائج تجارب قياسية لاختبار فعالية هذه الخوارزمية المقدمة.
In this research, we are studying the possibility of contribution in solving the multi-objective vehicle Routing problem with time windows , that is one of the optimization problems of the NP-hard type , This problem has attracted a lot of attention now because of its real life applications. Moreover, We will also introduced an algorithm called hybrid algorithm (HA) which depends on integrates between Multiple objective ant colony optimisation (MOACO) and tabu search (TS) algorithm based on the Pareto optimization , and compare the presented approach is the developer with standard tests to demonstrate the applicability and efficiency.
References used
DE ARMAS, J., MELI- BATISTA,B ., MORENO-PEREZ, J.A., BRITO, J ,. 2015 . Gvns for a real-world rich vehicle routing problem with time windows. Engineering Applications of Artificial Intelligence. (42),PP. 45-56
MOCCIA, L., CORDEAU,F., LAPORTE,G., 2012 An Incremental Tabu Search Heuristic for the Generalized Vehicle Routing Problem with Time Windows." Journal of the Operational Research Society. PP. 238-244
ARCHETTI,C.,SPERANZA,G.,2014.A survey on matheuristics for routing problem. EURO Journal on Computational Optimization, 2 :235–246
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In this research, we are studying the possibility of contribution in solving the Vehicle Routing Problem With Time Windows(VRPWTW), that is one of the optimization problems of the NP-hard type. This problem has attracted a lot of attention at the pre
sent time because of its real life applications. However, there is still no algorithm that provides us with the perfect solution to this problem because of the complexity of polynomial time. This means that the time of the solution to the Vehicle VRPWTW is growing steadily with the increase in the number of nodes .All the used algorithms have given solutions that are close to the optimal one . We'll introduce two algorithms , the first is Improved Ant Colony System algorithm (IACS) that is capable of searching multiple search areas simultaneously in the solution space is good in diversification ,and the second Simulated Annealing algorithm (SA) is a local search technique that has been successfully applied to many NP-hard problems. Moreover, we will present the In this research Hybrid algorithm (HA) Hybrid Algorithm provided (IACS-SA) that integrate between improved ant algorithm and Simulated Annealing algorithm . We will known standard tests are given to demonstrate the applicability and efficiency of the presented approach and comparisons with other available results are presented.
In this research, we are studying the possibility of
contribution in solving the Vehicle Routing Problem With Time
Windows(VRPWTW), that is one of the optimization problems of
the NP-hard type. This problem has attracted a lot of attention now
be
cause of its real life applications. However, there is still no
algorithm that provides us with the perfect solution to this problem
because of the complexity of polynomial time. This means that the
time of the solution to the VRPWTW is growing steadily with the
increase in the number of nodes .All the used algorithms have just
given solutions that are close to the optimal one.
In this research, we are studying the possibility of contribution in solving the Vehicle
Routing Problem with Time Windows(VRPTW),that is one of the optimization problems
of the NP-hard type.
Moreover, Hybrid algorithm (HA) provided that integrate
s between Tabu Search
Algorithm and Guided Local Search algorithm And existence 2- Opt Local Search, based
on the savings algorithm in terms of continued of a particular objective to provide a lot of
savings. As we will compare the presented approach with standard tests to demonstrate
the efficiency, and their impact on the quality of the solution in terms of speed of
convergence and the ability to find better solutions.
n this research, we are studying the possibility of contribution in solving the Vehicle Routing Problem (VRP), which is one of the optimization problems that, because of its Real Life applications, has attracted a lot of attention at the present tim
e. It is a problem of the NP-hard type. However, because of the complication of polynomial time there is still no algorithm providing us with the optimal solution of this problem. All the used algorithms give solutions that are close to the optimal one .
In this research, we will present the Hybrid Algorithm (HA) in two phases .In the first phase the Sweep Algorithm (SW) is applied, and in the second one the Ant Colony Algorithm and the local search 3-opt are applied. we will then compare the quality of the solution resulted from this hybrid approach with the results of well-known standard tests to determine the effectiveness of the presented approach .
Multi-objective evolutionary algorithms are used in a wide range
of fields to solve the issues of optimization, which require several
conflicting objectives to be considered together. Basic evolutionary
algorithm algorithms have several drawbacks,
such as lack of a
good criterion for termination, and lack of evidence of good
convergence. A multi-objective hybrid evolutionary algorithm is
often used to overcome these defects.
optimization
الأمثلة
الأمثلة متعددة الأهداف
الخوارزميات التطورية
الخوارزميات التطورية المتعددة الأهداف
الخوارزميات التطورية عديدة الأهداف
(Multi-Objective Optimization (MO
Evolutionary Algorithms
(Multi-Objective Evolutionary Algorithms (MOEAs
(Many-Objective Evolutionary Algorithms (MaOEAs
المزيد..
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