فهرس المقالات Traveling salesman problem

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  1 - توسعه مسأله فروشنده دوره گرد برای محصولات برگشتی با استفاده از الگوریتم خفاش (مطالعه موردی شرکت وزنه)
  Meisam Jafari Eskandari Ali Amouzad Khalili
  مسأله فروشنده دوره گرد یکی از مهم ترین مسائل در بهینه سازی ترکیباتی است که در بسیاری از علوم مهندسی مورد استفاده قرار می گیرد و توجه بسیاری از دانشمندان و محققین را به خود جلب کرده است. از جمله کاربردهای این مسأله بررسی مسائل حمل و نقل می باشد. در این مقاله با توسعه مدل أکثر

  مسأله فروشنده دوره گرد یکی از مهم ترین مسائل در بهینه سازی ترکیباتی است که در بسیاری از علوم مهندسی مورد استفاده قرار می گیرد و توجه بسیاری از دانشمندان و محققین را به خود جلب کرده است. از جمله کاربردهای این مسأله بررسی مسائل حمل و نقل می باشد. در این مقاله با توسعه مدل TSP برای کالاهای برگشتی به کارخانه در صدد کمینه سازی هزینه های ناشی از حمل و نقل هستیم. از آنجا که مدل به دست آمده از نوع NP-Hard است، برای حل آن از الگوریتم فراابتکاری خفاش استفاده می کنیم. تفاصيل المقالة
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  2 - A New Hybrid Parallel Simulated Annealing Algorithm for Travelling Salesman Problem with Multiple Transporters
  parham azimi Ramtin Rooeinfar Hani Pourvaziri
  In today’s competitive transportation systems, passengers search to find traveling agencies that are able to serve them efficiently considering both traveling time and transportation costs. In this paper, we present a new model for the traveling salesman problem w أکثر

  In today’s competitive transportation systems, passengers search to find traveling agencies that are able to serve them efficiently considering both traveling time and transportation costs. In this paper, we present a new model for the traveling salesman problem with multiple transporters (TSPMT). In the proposed model, which is more applicable than the traditional versions, each city has different transporting vehicles and the cost of travel through each city is dependent on the transporting vehicles type. The aim is to determine an optimal sequence of visited cities with minimum traveling times by available transporting vehicles within a limited budget. First, the mathematical model of TSPMT is presented. Next, since the problem is NP-hard, a new hybrid parallel simulated annealing algorithm with a new coding scheme is proposed. To analyze the performance of the proposed algorithm, 50 numerical examples with different budget types are examined and solved using the algorithm. The computational results of these comparisons show that the algorithm is an excellent approach in speed and solution quality. تفاصيل المقالة
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  3 - New Heuristic Algorithms for Solving Single-Vehicle and Multi-VehicleGeneralized Traveling Salesman Problems (GTSP)
  Ellips Masehian
  Among numerous NP-hard problems, the Traveling Salesman Problem (TSP) has been one of the most explored, yet unknown one. Even a minor modification changes the problem’s status, calling for a different solution. The Generalized Traveling Salesman Problem (GTSP)expands أکثر

  Among numerous NP-hard problems, the Traveling Salesman Problem (TSP) has been one of the most explored, yet unknown one. Even a minor modification changes the problem’s status, calling for a different solution. The Generalized Traveling Salesman Problem (GTSP)expands the TSP to a much more complicated form, replacing single nodes with a group or cluster of nodes, where the objective is to find a minimum-length tour containing exactly one node from each cluster. In this paper, a new heuristic method is presented for solving singlevehicle single-depot GTSP with the ability of controlling the search strategy from conservative to greedy and vice versa. A variant algorithm is then developed to accommodate the multi-vehicle single-depot condition, which is modified afterwards to accommodate the multi-vehicle multi-depot GTSP. تفاصيل المقالة
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  4 - Solving the Multiple Traveling Salesman Problem by a Novel Meta-heuristic Algorithm
  Hossein Larki Majid Yousefikhoshbakht
  The multiple traveling salesman problem (MTSP) is a generalization of the famous traveling salesman problem (TSP), where more than one salesman is used in the solution. Although the MTSP is a typical kind of computationally complex combinatorial optimization problem, it أکثر

  The multiple traveling salesman problem (MTSP) is a generalization of the famous traveling salesman problem (TSP), where more than one salesman is used in the solution. Although the MTSP is a typical kind of computationally complex combinatorial optimization problem, it can be extended to a wide variety of routing problems. This paper presents an efficient and evolutionary optimization algorithm which has been developed through combining Modified Imperialist Competitive Algorithm and Lin-Kernigan Algorithm (MICA) in order to solve the MTSP. In the proposed algorithm, an absorption function and several local search algorithms as a revolution operator are used. The performance of our algorithm was tested on several MTSP benchmark problems and the results confirmed that the MICA performs well and is quite competitive with other meta-heuristic algorithms. تفاصيل المقالة
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  5 - An Effective Genetic Algorithm for Solving the Multiple Traveling Salesman Problem
  Mohammad Sedighpour Majid Yousefikhoshbakht Narges Mahmoodi Darani
  The multiple traveling salesman problem (MTSP) involves scheduling m > 1 salesmen to visit a set of n > m nodes so that each node is visited exactly once. The objective is to minimize the total distance traveled by all the salesmen. The MTSP is an example of combi أکثر

  The multiple traveling salesman problem (MTSP) involves scheduling m > 1 salesmen to visit a set of n > m nodes so that each node is visited exactly once. The objective is to minimize the total distance traveled by all the salesmen. The MTSP is an example of combinatorial optimization problems, and has a multiplicity of applications, mostly in the areas of routing and scheduling. In this paper, a modified hybrid metaheuristic algorithm called GA2OPT for solving the MTSP is proposed. In this algorithm, at the first stage, the MTSP is solved by the modified genetic Algorithm (GA) in each iteration, and, at the second stage, the 2-Opt local search algorithm is used for improving solutions for that iteration. The proposed algorithm was tested on a set of 6 benchmark instances from the TSPLIB and in all but four instances the best known solution was improved. For the rest instances, the quality of the produced solution deviates less than 0.01% from the best known solutions ever. تفاصيل المقالة
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  6 - Integrating Case-Based Reasoning, Knowledge-Based Approach and TSP Algorithm for Minimum Tour Finding
  حسین عرفانی
  Imagine you have traveled to an unfamiliar city. Before you start your daily tour around the city, you need to know a good route. In Network Theory (NT), this is the traveling salesman problem (TSP). A dynamic programming algorithm is often used for solving this problem أکثر

  Imagine you have traveled to an unfamiliar city. Before you start your daily tour around the city, you need to know a good route. In Network Theory (NT), this is the traveling salesman problem (TSP). A dynamic programming algorithm is often used for solving this problem. However, when the road network of the city is very complicated and dense, which is usually the case, it will take too long for the algorithm to find the shortest path. Furthermore, in reality, things are not as simple as those stated in AT. For instance, the cost of travel for the same part of the city at different times may not be the same. In this project, we have integrated TSP algorithm with AI knowledge-based approach and case-based reasoning in solving the problem. With this integration, knowledge about the geographical information and past cases are used to help TSP algorithm in finding a solution. This approach dramatically reduces the computation time required for minimum tour finding. تفاصيل المقالة
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  7 - An Effective Ant Colony Algorithm for the Traveling Salesman Problem
  Majid Yousefikhoshbakht Azam Dolatnejad
  The traveling salesman problem (TSP) is a well-known combinatorial optimization problem and holds a central place in logistics management. The TSP has received much attention because of its practical applications in industrial problems. Many exact, heuristic and metaheu أکثر

  The traveling salesman problem (TSP) is a well-known combinatorial optimization problem and holds a central place in logistics management. The TSP has received much attention because of its practical applications in industrial problems. Many exact, heuristic and metaheuristic approaches have been proposed to solve TSP in recent years. In this paper, a modified ant colony optimization (MACO) is presented which possesses a new strategy to update the increased pheromone, a candidate list and a mutation operation to solve the TSP. In addition, some local search algorithms are utilized as an effective criterion and only a global updating is used in order to increase pheromone on the edges of the best route. The proposed metaheuristic algorithm is tested on the well-known TSP instances involving 14 benchmark problems from 48 to 200 nodes. The computational results show that our algorithm is better than other meta-heuristic algorithms in terms of solution quality. Furthermore, the gap of the proposed algorithm stays on average almost 1% of the execution time and also the most best known solutions of the benchmark problems are found. تفاصيل المقالة
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  8 - A modified elite ACO based avoiding premature convergence for travelling salesmen problem
  M Yousefikhoshbakht E Mahmoodabadi M Sedighpour
  The Travelling Salesmen Problem (TSP) is one of the most important and famous combinational optimization problems that aim to find the shortest tour. In this problem, the salesman starts to move from an arbitrary place called depot and after visiting all nodes, finally أکثر

  The Travelling Salesmen Problem (TSP) is one of the most important and famous combinational optimization problems that aim to find the shortest tour. In this problem, the salesman starts to move from an arbitrary place called depot and after visiting all nodes, finally comes back to depot. Solving this problem seems hard because program statement is simple and leads this problem belonging to NP-hard programs.In this paper, the researchers present a modified Elite Ant System (EAS) which is different from common EAS. There is a linear function used here for increasing coefficient pheromone of the best route activated when a better solution is achieved. This process will avoid the premature convergence and makes better solutions. The results on several standard instances show that this new algorithm would gain more efficient solutions compared to other algorithms. تفاصيل المقالة