Vehicle routing problem is one of the most important issues in transportation. Among VRP problems, the competitive VRP is more important because there is a tough competition between distributors and retailers. In this study we introduced new method for VRP in competitive environment. In these methods Two-Person Nonzero Sum games are defined to choose equilibrium solution. Therefore, revenue giv...

We propose an algorithmic framework that successfully addresses three vehicle routing problems: the multi-depot VRP, the periodic VRP, and the multi-depot periodic VRP with capacitated vehicles and constrained route duration. The meta-heuristic combines the exploration breadth of population-based evolutionary search, the aggressive improvement capabilities of neighborhood-based meta-heuristics,...

The Vehicle Routing Problem (VRP) is a NP-hard and Combinatorial optimization problem. Combinatorial optimization problem can be viewed as searching for best element in a set of discrete items, which can be solved using search algorithm or meta heuristic. In this work, VRP is solved using population based search algorithm, Particle Swarm Optimization (PSO) with crossover and mutation operators....

This paper introduces a parallel iterated tabu search heuristic for solving four different routing problems: the classical vehicle routing problem (VRP), the periodic VRP, the multi-depot VRP, and the site-dependent VRP. In addition, it is applicable to the time-window constrained variant of these problems. Using the iterated local search framework, the heuristic combines tabu search with a sim...

The vehicle routing problem (VRP) is one of the most challenging problems in the optimization of distribution networks. A distribution model, based on analysis of most published literatures, relevant to route arrangement was established for VRP. Meantime, an improved genetic algorithm (IGA) was proposed to overcome both the shortcomings of premature convergence of GA and local search. Inversion...

The vehicle routing problem (VRP) is an important problem in the field of logistics management. As an NP-hard problem, the VRP real world sized instances cannot be solved to optimality within reasonable times. This research aims to develop a two-stage ant colony optimization (TACO) algorithm, which possesses a two-stage solution construction rule, to solve the large scale vehicle routing proble...

Title of dissertation: INTEGER PROGRAMMING-BASED HEURISTICS FOR VEHICLE ROUTING PROBLEMS Damon J. Gulczynski Doctor of Philosophy, 2010 Dissertation directed by: Professor Bruce Golden Applied Mathematics and Scientific Computation Robert H. Smith School of Business The vehicle routing problem (VRP) has been an active field of study by operations researchers for over 50 years. Many practical ap...

The vehicle routing problem (VRP), a well-known combinatorial optimization problem, holds a central place in logistics management. Many meta-heuristic approaches like Simulated Annealing (SA), Genetic Algorithms (GA), Tabu Search (TS), and Ant Colony Optimization (ACO) have been proposed to solve VRP. Ant Algorithm is a distributed meta-heuristic approach that has been applied to various combin...

Genetic Vehicle Representation (GVR) is a two level representational scheme, designed to deal in an effective way with all the information needed by candidate solutions, for the Vehicle Routing Problem (VRP). In this paper, we present an analysis on the influence of two crossover operators in the algorithm performance. A first study on diversity is also presented, regarding the issues of divers...

The ship routing problem (SRP) is a special variant of the classical vehicle routing problems (VRPs), which is different from both the VRP with backhauls (VRPB) and the VRP with pickup and delivery (VRPPD). This paper proposes a new immune genetic algorithm for the large scale SRP. The backhaul and time window constraints are also considered. The immune GA is innovated based on the classic GA a...