A genetic algorithm for the generalised assignment problem
Computers and Operations Research
Supply-Chain Analysis at Volkswagen of America
Interfaces - supply-chain management
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms
On the use of genetic algorithms to solve location problems
Computers and Operations Research - Location analysis
Information Sciences: an International Journal
Computers and Industrial Engineering
Expert Systems with Applications: An International Journal
Review article: A review of soft computing applications in supply chain management
Applied Soft Computing
Journal of Intelligent Manufacturing
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Third party logistics service providers (3PLs) are playing an increasing role in the management of supply chains. Especially in warehousing and transportation services, a number of clients expect for 3PLs to improve lead times, fill rates, inventory levels, etc. Hence, these 3PLs are under pressure to meet various clients' service requirements in a dynamic and uncertain business environment. As a result, 3PLs should maintain an efficient distribution system of high performance competitive advantages. In this paper, we propose a hybrid optimization/simulation approach to design a distribution network for 3PLs in consideration of the performance of the warehouses. The optimization model uses a genetic algorithm to determine dynamic distribution network structures. Subsequently, the simulation model is applied to capture the uncertainty in clients' demands, order-picking time, and travel time for the capacity plans of the warehouses based on service time. The approach is applied to an example problem for examining its validity.