Abstract
This paper studies the simultaneous dock assignment and sequencing of inbound trucks for a multi-door cross docking operation with the objective to minimize total weighted tardiness, under a fixed outbound truck departure schedule. The problem is newly formulated and solved by six different metaheuristic algorithms, which include simulated annealing, tabu search, ant colony optimization, differential evolution, and two hybrid differential- evolution algorithms. To evaluate the total weighted tardiness associated with any given inbound-truck sequence and dock assignment, an operational policy is developed. This policy is employed by every metaheuristic algorithm in searching for the optimal dock assignment and sequence. Each metaheuristic algorithm is tested with 40 problems. The major conclusions are: (1) metaheuristic is generally an effective optimization method for the subject problem; (2) population based metaheuristic algorithms are generally more effective than projection based metaheuristic algorithms; (3) proper selection of algorithmic parameters is important and more critical for projection based metaheuristic algorithms than population based algorithms; (4) the two best algorithms are ant colony optimization and hybrid differential evolution 2; among them, ACO takes less time than hybrid 2 and thus can be declared the best among all the six metaheuristic algorithms tested.
Original language | English (US) |
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Pages (from-to) | 212-229 |
Number of pages | 18 |
Journal | International Journal of Production Economics |
Volume | 141 |
Issue number | 1 |
DOIs | |
State | Published - Jan 2013 |
All Science Journal Classification (ASJC) codes
- General Business, Management and Accounting
- Economics and Econometrics
- Management Science and Operations Research
- Industrial and Manufacturing Engineering
Keywords
- Ant colony optimization
- Combinatorial optimization
- Cross docking
- Differential evolution
- Dock assignment
- Hybrid metaheuristics
- Sequencing
- Simulated annealing
- Tabu search