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In order to effectively prevent particle swarm into local optimum and enhance the ability of particles to find the optimal solution, the paper proposes an improved particle swarm algorithm. The paper is on the background of vehicle scheduling, which is using the load priority strategy, and establishes the model for vehicle scheduling problem with load and vehicle scheduling problem with soft time...
Although a significant amount of research has focused on the use of Artificial Neural Networks (ANNs) for solving the Traveling Salesman Problem (TSP), there is considerably less attention on the application of ANNs to the Vehicle Routing Problem (VRP). This paper proposes an updated Self Organizing Map approach to solving the Capacitated Vehicle Routing Problem (CVRP). The proposed algorithm extends...
Capacitated vehicle routing problem with pickups and deliveries (CVRPPD) is one of the most challenging combinatorial optimization problems which include goods delivery/pickup optimization, vehicle number optimization, routing path optimization and transportation cost minimization. The conventional particle swarm optimization (PSO) is difficult to find an optimal solution of the CVRPPD due to its...
We introduce an improved intelligent water drops (IIWD) algorithm as a new swarm-based nature inspired algorithm to solve capacitated vehicle routing problem. IIWD algorithm introduces new adjustments and features that help to optimize the VRP problem with higher efficiency. We reinforce this algorithm to have satisfactory consequences in controlling the balance between diversification and intensification...
Vehicle Routing Problem (VRP) is a famous combinatorial optimization problem and it has been extended to a multi-objective optimization perspective. This paper targets solving VRP with stochastic demand (VRPSD) under the constraints of available time window and vehicle capacity. The objective of the problem is to simultaneously minimize total travelling distance and total drivers' remuneration. This...
Thi s paper presents an enhanced version of Ant Colony Optimization (ACO) for solving a variant of the Vehicle Routing Problem (VRP), which is utilized for Unmanned Aerial Vehicle (UAV) task allocation and route planning. The extended VRP incorporates multiple UAVs, collision avoidance between intersecting routes, and the possibility of loitering between tasks. The ACO adopts a multi-colony approach...
Vehicle Routing Problem (VRP) is a well known NP-hard optimization problem with a number of real world applications and a variety of different versions. Due to its complexity, large instances of VRP are hard to solve using exact methods. Instead, various heuristic and meta-heuristic algorithms were used to find feasible VRP solutions. This work proposes a Differential Evolution for VRP that simultaneously...
The artificial bee colony algorithm (ABC) with three loading heuristics for the two-dimensional loading capacitated vehicle routing problem (2L-CVRP) is presented in the paper. The 2L-CVRP is a combination of two well-known NP-hard problems, the capacitated vehicle routing problem, and the two-dimensional bin packing problem. It is very difficult to get a good performance solution in practice for...
In this paper, a new evolutionary algorithm called common grounding optimization (CGO) is proposed for capacitated vehicle routing problem (CVRP). The algorithm consists of three main operations: common ground seeking, encapsulating, and iterated local search (ILS). The algorithm is population-based with all the individual solutions eventually converge to the same optimal value. Experimental results...
The unidirectional logistics distribution vehicle routing problem with no time windows is considered. It contains the vehicle capacity restriction, the longest distance restriction and the full loaded vehicle. The solution must ensure the non-full loaded factor is the least and the total distance is the shortest. A multi-objective optimization mathematical model for the problem is established. And...
Provides a novel hybrid ant colony algorithm combining genetic algorithm with implicit parallel function to make up the shortcomings of common ant colony alogrithm in the vehicle routing problem including slow convergence in the early stages. Introducing the encoding and mutation operation can improve the efficiency of solving the optimal distribution path. The comparative analysis of vehicle routing...
Vehicle routing problem is a combinatorial optimization problem and is known as NP-complete. Among many proposed schemes, meta-heuristic algorithms are prospective for solving NP problems. Hence, a modified ant colony optimization (ACO) is proposed to solve a type of vehicle routing problem named capacitated vehicle routing problem (CVRP) which involves minimization of the total routing distance by...
Ant colony algorithm is a kind of novel simulation-biological evolution algorithm. An improved ant colony algorithm was utilized to solve the vehicle routing problem in emergency logistics. Genetic algorithm was utilized to optimize the parameters of ant colony algorithm. The algorithm possesses some characteristics such as strong total researching ability. The experimental results show that the improved...
Hysteretic optimization (HO) is a recently proposed heuristic physical optimization algorithm based on the well-known demagnetization process of magnetic materials in magnetism. The Capacitated Vehicle Routing Problem (CVRP) is an important variant of the vehicle routing problem which is one of the most important and intensively studied combinatorial optimization problems. In this study, we apply...
Despite the fact that the vehicle routing problem (VRP) with its variants has been widely explored in operations research, there is very little published research on the VRP concerning real world constraint combinations and large problem sizes. In this work a heuristic solution approach for the VRP with real world constraints is presented driven by the requirements defined by clients in the courier,...
The paper presents selected aspects of a single-depot vehicle routing problem with multi-commodity heterogeneous suppliers demand. Main attention is paid to the problem of certain goods groups transport on the same vehicle. To solve this problem each supplier is characterized by a different goods group which is in his possession. Also the structure and the characteristics of a goods transportation...
For vehicle routing problem (VRP), an algorithm based on bee evolutionary particle swarm (BEPSO) was presented and applied to VRP. In this algorithm, the best particle which was regarded as queen cross with selected drones in a random probability, enhancing application ability of the best individual's information. At the same time, some drones were randomly generated and crossed with the queen, which...
Vehicle Routing Problem is the NP problem,and only can it get precise optimum when the problem is simple, so the intelligent elicitation algorithm becomes an important studied field. This paper adopts PSO to optimize VRP. The local search capacity of PSO is relatively weak,so this paper combines PSO with simulated annealing and designs the PSO based on SA using the characteristics that SA can accept...
Based on in-depth investigation and study of product distribution system of a food factory in Nanjing city, the distribution status including distribution of the enterprise product line, distribution volume and vehicle utilization were analyzed and existing problems were pointed out. Strategies were put forward according to the factory distributing status, to help improve vehicle efficiency and reduce...
The vehicle routing problem is proved to be a kind of NP problem. Immune genetic algorithm is proposed based on genetic algorithm and the use of the biological and immune system in this paper. A kind of group diversity maintaining strategy based on the density of individual is constructed. An immune operator and a immune memory library are applied to the algorithm. The experimental results of a VRP...
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