Vehicle Routing problem is very important and logistic in combinatorial optimization. In this paper, an innovative algorithm that combines the colony of ants and mutation operation for vehicle Routing problem is presented.

Routing is an important challenge in WSN due to the presence of hundreds or thousands of sensor nodes. Low Energy Adaptive Clustering Hierarchy (LEACH) is a hierarchical Routing and data dissemination protocol. LEACH divides a network domain into several sub-domains that are called clusters. Non-uniformity of cluster distribution and cluster heads (CHs) selection without considering the positions of other sensors may reduce the quality of cluster selection. Sensor nodes send data packets over long distances. Imperialist Competitive algorithm (ICA) is an optimization algorithm inspired by social phenomenon. It considers colonization process as a stage of socio-political evolution. We improve performance of the LEACH algorithm using imperialist approach and study its efficacy in terms of energy consumption, coverage and cluster uniformity and compare with those of the LEACH algorithm. Selection of suitable value for radio communication radius over the network lifetime is a trade-off between connectivity and sensors energy consumption. Empowering LEACH with ICA helps to find the best location of a CH in every cluster, conserve energy significantly, increase network lifetime, and maintain network connectivity. It can significantly reduce the number of active sensors going out of range over the lifetime of a network.

In this paper, a new algorithm for solving the single loop Routing problem is presented. The purpose of the single loop Routing problem(SLRP) Is to find the shortest loop for an automated guided vehicle covering at least one edge of each department of a block layout. First it shown that this problem can be represented as a graph model Then a meta-heuristic algorithm based on and colony system is developed for ALRP by using the properties of the graph model. Computational results show the efficiency of the proposed algorithm in comparison with other techniques for solving SLRP.

The open vehicle Routing problem (OVRP) is a variance of the vehicle Routing problem (VRP) that has a unique character which is its open path form. This means that the vehicles are not required to return to the depot after completing service. Because this problem belongs to the NP-hard problems, many metaheuristic approaches like the ant colony optimization (ACO) have been used to solve OVRP in recent years. The versions of ACO have some shortcomings like its slow computing speed and local-convergence. Therefore, in this paper, we present an efficient hybrid elite ant system called EHEAS in which a new state transition rule, tabu search as an effective local search algorithm and a new pheromone updating rule are used for more improving solutions. These modifications avoid the premature convergence and make better solutions. Computational results on sixteen standard benchmark problem instances show that the proposed algorithm finds closely the best known solutions for most of the instances in which ten best known solutions are also found. In addition, EHEAS is comparable in terms of solution quality to the best performing published metaheuristics.

The vehicle Routing problem with the capacity constraints was considered in this paper. It is quite difficult to achieve an optimal solution with traditional optimization methods by reason of the high computational complexity for large-scale problems. Consequently, new heuristic or metaheuristic approaches have been developed to solve this problem. In this paper, we constructed a new heuristic algorithm based on the tabu search and adaptive large neighborhood search (ALNS) with several specifically designed operators and features to solve the capacitated vehicle Routing problem (CVRP). The effectiveness of the proposed algorithm was illustrated on the benchmark problems.The algorithm provides a better performance on largescaled instances and gained advantage in terms of CPU time.In addition, we solved a real-life CVRP using the proposed algorithm and found the encouraging results by comparison with the current situation that the company is in.

Recently, underwater Wireless Sensor Networks (UWSNs) attracted the interest of many researchers and the past three decades have held the rapid progress of underwater acoustic communication. One of the major problems in UWSNs is how to transfer data from the mobile node to the base stations and choosing the optimized route for data transmission. Secure Routing in UWSNs is necessary for packet delivery. A few researches have been done on secure Routing in UWSNs. In this article, a new secure Routing algorithm called Secure Routing algorithm for Underwater (SRAU) sensor networks is proposed to resist against wormhole and sybil attacks. The results indicate acceptable performance in terms of increasing the packet delivery ratio regarding the wormhole and sybil attacks, increasing network lifetime through balancing the network energy consumption, high detection rates against the attacks, and decreasing the end to end delay.

A significant portion of Gross Domestic Production (GDP) in any country belongs to the transportation system. Transportation equipment, is supposed to be great consumer of oil products. In this papera novel heuristic algorithmbased on Clark and Wright algorithm called Green Clark and Wright (GCW) for Green Vehicle Routing Problem is presented. The objective function is fuel consumption, drivers, and the usage of vehicles. Comparing obtained results by those of exact methods solutions for small-sized problems and Differential Evolution (DE) algorithm solutions for large-scaled problems, the results show efficient performance of the proposed GCW algorithm.

Different types of contact, including contact between node pairs, any-contact of nodes, and contacts of the entire network, are used to characterize social relations in mobile social networks. Different modes of Routing, from the point of view of message delivery semantics, encompass unicasting, multicasting, any-casting, and broadcasting. Studies have shown that using probability distribution functions of contact data, which is mainly assumed to be homogeneous for nodes, improves the performance of these networks. However, there exists an important challenge in studies on distributions. A lot of works apply the distribution of one type of contact to other types. Hence in Routing applications, it causes to use of the distribution of one type of contact for any mode of Routing. This study provides a complete solution to model each type of homogeneous contact data distribution and to use them in different modes of Routing. We propose a Routing algorithm that uses this new model. Results show that our solution improves the average latency of comparing methods Epidemic, TCCB, and DR about 3.5-times, 30%, and 45%, respectively. It achieves a delivery rate of about 5% and 6%, and average latency about 6% and 8% better than that of DR and TCCB, respectively.

Periodic vehicle Routing problem focuses on establishing a plan of visits to clients over a given time horizon so as to satisfy some service level while optimizing the routes used in each time period. This paper presents a new effective heuristic algorithm based on data mining tools for periodic vehicle Routing problem (PVRP). The related results of proposed algorithm are compared with the results obtained by best Heuristics and meta-heuristics algorithms in the literature. Computational results indicate that the algorithm performs well in terms of accuracy and solution time.