Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
MACS-VRPTW: a multiple ant colony system for vehicle routing problems with time windows
New ideas in optimization
A Survey of Optimization Models for Train Routing and Scheduling
Transportation Science
Railway Timetabling Using Lagrangian Relaxation
Transportation Science
A Benders Decomposition Approach for the Locomotive and Car Assignment Problem
Transportation Science
Simultaneous Assignment of Locomotives and Cars to Passenger Trains
Operations Research
An Improved Branch-and-Cut Algorithm for the Capacitated Vehicle Routing Problem
Transportation Science
Very large-scale vehicle routing: new test problems, algorithms, and results
Computers and Operations Research
Multi-Objective Genetic Algorithms for Vehicle Routing Problem with Time Windows
Applied Intelligence
A Hybrid Multiobjective Evolutionary Algorithm for Solving Vehicle Routing Problem with Time Windows
Computational Optimization and Applications
Sequential search and its application to vehicle-routing problems
Computers and Operations Research
Waste collection vehicle routing problem with time windows
Computers and Operations Research
A general heuristic for vehicle routing problems
Computers and Operations Research
Solving Real-Life Locomotive-Scheduling Problems
Transportation Science
A hybrid genetic algorithm for the capacitated vehicle routing problem
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Parallel simulated annealing for the vehicle routing problem with time windows
EUROMICRO-PDP'02 Proceedings of the 10th Euromicro conference on Parallel, distributed and network-based processing
An evolutionary-based approach for solving a capacitated hub location problem
Applied Soft Computing
A revision algorithm for invalid encodings in concurrent formation of overlapping coalitions
Applied Soft Computing
The periodicity and robustness in a single-track train scheduling problem
Applied Soft Computing
Journal of Mathematical Modelling and Algorithms
Expert Systems with Applications: An International Journal
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This paper presents a hybrid genetic algorithm to solve a multi-depot homogenous locomotive assignment problem with time windows. The locomotive assignment problem is to assign a set of homogeneous locomotives locating in a set of dispersed depots to a set of pre-schedules trains that are supposed to be serviced in pre-specified hard/soft time windows. A mathematical model is presented, using vehicle routing problem with time windows (VRPTW) for formulation of the problem. A cluster-first, route-second approach is used to inform the multi-depot locomotive assignment to a set of single depot problems and after that we solve each problem independently. Each single depot problem is solved heuristically by a hybrid genetic algorithm that in which Push Forward Insertion Heuristic (PFIH) is used to determine the initial solution and @l-interchange mechanism is used for neighborhood search and improving method. A medium sized numerical example with different scenarios is presented and examined to more clarification of the approach as well as to check capabilities of the model and algorithm. Also some of the results are compared with the solutions produced by branch & bound technique to determine validity and quality of the model. The experiments with a set of 15 completely random generated instance problems indicate that this algorithm is efficient and solves the problem in a polynomial time.