A general heuristic for vehicle routing problems
Computers and Operations Research
The vehicle routing problem with flexible time windows and traveling times
Discrete Applied Mathematics - Special issue: Discrete algorithms and optimization, in honor of professor Toshihide Ibaraki at his retirement from Kyoto University
Active guided evolution strategies for large-scale vehicle routing problems with time windows
Computers and Operations Research
Vehicle Routing Problem with Time Windows, Part II: Metaheuristics
Transportation Science
Computers and Operations Research
Discrete Applied Mathematics
A Column Generation Algorithm for a Rich Vehicle-Routing Problem
Transportation Science
Iterated local search for the team orienteering problem with time windows
Computers and Operations Research
A penalty-based edge assembly memetic algorithm for the vehicle routing problem with time windows
Computers and Operations Research
Arc-guided evolutionary algorithm for the vehicle routing problem with time windows
IEEE Transactions on Evolutionary Computation
Computers and Operations Research
EvoCOP'08 Proceedings of the 8th European conference on Evolutionary computation in combinatorial optimization
A variable neighborhood descent heuristic for arc routing problems with time-dependent service costs
Computers and Industrial Engineering
Survey: matheuristics for rich vehicle routing problems
HM'10 Proceedings of the 7th international conference on Hybrid metaheuristics
A cross entropy multiagent learning algorithm for solving vehicle routing problems with time windows
ICCL'11 Proceedings of the Second international conference on Computational logistics
HM'06 Proceedings of the Third international conference on Hybrid Metaheuristics
Computers and Industrial Engineering
Computers and Operations Research
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We propose local search algorithms for the vehicle routing problem with soft time-window constraints. The time-window constraint for each customer is treated as a penalty function, which is very general in the sense that it can be nonconvex and discontinuous as long as it is piecewise linear. In our algorithm, we use local search to assign customers to vehicles and to find orders of customers for vehicles to visit. Our algorithm employs an advanced neighborhood, called the cyclic-exchange neighborhood, in addition to standard neighborhoods for the vehicle routing problem. After fixing the order of customers for a vehicle to visit, we must determine the optimal start times of processing at customers so that the total penalty is minimized. We show that this problem can be efficiently solved by using dynamic programming, which is then incorporated in our algorithm. We report computational results for various benchmark instances of the vehicle routing problem. The generality of time-window constraints allows us to handle a wide variety of scheduling problems. As an example, we mention in this paper an application to a production scheduling problem with inventory cost, and report computational results for real-world instances.