Mixed-Integer Nonlinear Programming for Energy-Efficient Container Handling: Formulation and Customized Genetic Algorithm

Energy consumption is expected to be reduced while maintaining high productivity for container handling. This paper investigates a new energy-efficient scheduling problem of automated container terminals, in which quay cranes (QCs) and lift automated guided vehicles (AGVs) cooperate to handle inboun...

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Vydané v:IEEE transactions on intelligent transportation systems Ročník 23; číslo 8; s. 10542 - 10555
Hlavní autori: Xin, Jianbin, Meng, Chuang, D'Ariano, Andrea, Wang, Dongshu, Negenborn, Rudy R.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.08.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Automated container terminals
Automated guided vehicles
Containers
Cranes
Customization
Energy consumption
energy efficiency
genetic algorithm
Genetic algorithms
Handling
Heuristic methods
Job shop scheduling
Mixed integer
mixed-integer nonlinear programming
Nonlinear programming
Optimization
Task analysis
Task scheduling
Transport buildings, stations and terminals
ISSN:1524-9050, 1558-0016
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Shrnutí:Energy consumption is expected to be reduced while maintaining high productivity for container handling. This paper investigates a new energy-efficient scheduling problem of automated container terminals, in which quay cranes (QCs) and lift automated guided vehicles (AGVs) cooperate to handle inbound and outbound containers. In our scheduling problem, operation times and task sequences are both to be determined. The underlying optimization problem is mixed-integer nonlinear programming (MINLP). To deal with its computational intractability, a customized and efficient genetic algorithm (GA) is developed to solve the studied MINLP problem, and lexicographic and weighted-sum strategies are further considered. An <inline-formula> <tex-math notation="LaTeX">\epsilon </tex-math></inline-formula>-constraint algorithm is also developed to analyze the Pareto frontiers. Comprehensive experiments are tested on a container handling benchmark system, and the results show the effectiveness of the proposed lexicographic GA, compared to results obtained with two commonly-used metaheuristics, a commercial MINLP solver, and two state-of-the-art methods.
Bibliografia:ObjectType-Article-1
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content type line 14
ISSN:1524-9050
1558-0016
DOI:10.1109/TITS.2021.3094815