Optimization of control parameters for genetic algorithms
IEEE Transactions on Systems, Man and Cybernetics
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Vehicle routing with pick-up and delivery: tour-partitioning heuristics
Computers and Industrial Engineering
A tabu search algorithm for the vehicle routing problem
Computers and Operations Research
Toward Self-Integrating Software Applications for Supply Chain Management
Information Systems Frontiers
An Electromagnetism-like Mechanism for Global Optimization
Journal of Global Optimization
Vehicle routing scheduling for cross-docking in the supply chain
Computers and Industrial Engineering - Special issue: Logistics and supply chain management
Evolutionary algorithms for constrained parameter optimization problems
Evolutionary Computation
Parameter control in evolutionary algorithms
IEEE Transactions on Evolutionary Computation
Expert Systems with Applications: An International Journal
Multi-objective genetic-based algorithms for a cross-docking scheduling problem
Applied Soft Computing
Layout and control policies for cross docking operations
Computers and Industrial Engineering
Optimizing replenishment polices using Genetic Algorithm for single-warehouse multi-retailer system
Expert Systems with Applications: An International Journal
Vehicle routing scheduling using an enhanced hybrid optimization approach
Journal of Intelligent Manufacturing
Expert Systems with Applications: An International Journal
Robust door assignment in less-than-truckload terminals
Computers and Industrial Engineering
Three-stage hybrid-flowshop model for cross-docking
Computers and Operations Research
Approximation Algorithms for Capacitated Location Routing
Transportation Science
Analysis of different approaches to cross-dock truck scheduling with truck arrival time uncertainty
Computers and Industrial Engineering
Expert Systems with Applications: An International Journal
A tabu search approach to the truck scheduling problem with multiple docks and time windows
Computers and Industrial Engineering
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Cross-docking is a logistics technique that minimizes the storage and order picking functions of a warehouse while still allowing it to serve its receiving and shipping functions. The idea is to transfer shipments directly from incoming to outgoing trailers without storage in between. In this paper we apply five meta-heuristic algorithms: genetic algorithm (GA), tabu search (TS), simulated annealing (SA), electromagnetism-like algorithm (EMA) and variable neighbourhood search (VNS) to schedule the trucks in cross-dock systems such that minimize total operation time when a temporary storage buffer to hold items temporarily is located at the shipping dock. A design procedure is developed to specify and adjust significant parameters for GA, TS, SA, EMA and VNS. The proposed procedure is based on the response surface methodology (RSM). Two different types of objective functions are considered to develop multiple objective decision making model. For the purpose of comparing meta-heuristics, makespan and CPU time are considered as two response variables representing effectiveness and efficiency of the algorithms. Based on obtained results, VNS is recommended for scheduling trucks in cross-docking systems. Also, since for real size problems, it is not possible to reach optimum solution, a lower bound is presented to evaluate the resultant solutions.