Container Terminal Oriented Logistics Generalized Computational Complexity

Bin Li, Bing Sun, Wei Yao, Yuqing He, Guanggang Song
2019 IEEE Access  
The planning and scheduling of container terminal logistics systems (CTLS) are the multiobjective and multiple strong constraints combinatorial optimization challenges under the uncertain environments, and those are provided with high goal orientation, dynamics, context-sensitivity, coupling, timeliness, and complexity. The increasingly sophisticated decision-making for CTLS is one of the most pressing problems for the programming and optimization method available. This paper discusses CTLS in
more » ... erms of logistics generalized computation complexity based on computational thinking, great principles of computing, and computational lens, which three are abbreviated with 3CTGPL, and makes a definition of container terminal oriented logistics generalized computational complexity (CTO-LGCC) and container terminal logistics generalized computation comprehensive performance perspective (CTL-GCCPP) from the dimensions of time, space, communication, processor, and memory access. Both can analyze, generalize, migrate, translate, localize, modificate, and evaluate the above-complicated problems and lay solid foundations and establish a feedback improvement framework for the computational model and scheduling algorithms of the CTLS, which is an essential complement to the modeling and optimization methodology and solutions to CTLS with computational logistics. Finally, aimed at the logistics service cases for a largescale container terminal, the simulation is designed and implemented for different scheduling algorithms, and the qualitative and quantitative comprehensive analysis is executed for the concomitant CTO-LGCC that demonstrates and verifies the feasibility and credibility of the CTO-LGCC and CTL-GCCPP from the viewpoint of the practice of container terminal decision-making support on the tactical level. INDEX TERMS Logistics, scheduling, freight containers, computational modeling, computational complexity, decision making, numerical simulation, computational logistics, logistics generalized computation for container terminal. 94738 VOLUME 7, 2019
doi:10.1109/access.2019.2928684 fatcat:6bqd74cpdfaylkpga3byg7peiq