Table of Content

30 September 2020, Volume 8 Issue 3

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Preface: Special Issue on Operations Research Models and Algorithms in Transportation

Lu Zhen

2020, 8(3):  353-355.  doi:10.1007/s40305-020-00321-w

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A Decision Framework for Automatic Guided Vehicle Routing Problem with Traffic Congestions

Lu Zhen, Yi-Wei Wu, Si Zhang, Qiu-Ji Sun, Qi Yue

2020, 8(3):  357-373.  doi:10.1007/s40305-018-0216-4

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Automatic guided vehicles are widely used in various types of warehouses including the automated container terminals. This paper provides a decision framework for port managers to design and schedule automatic guided vehicle routing plans under timevarying traffic conditions. A large number of computational experiments on a grid graph are conducted to validate the efficiency of the proposed decision framework. We also proposed one efficient queueing rule in automatic guided vehicle routing scheduling. Although the complexity of the problem is high, computational results show that our proposed decision framework can provide high quality solutions within a relatively short computation time.

Simulation Analyses of Two On-Ramp Lane Arrangements

Xu Wang, Xiao-Bo Qu, Pan Li

2020, 8(3):  375-390.  doi:10.1007/s40305-018-0217-3

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Ramps are vital pieces of infrastructure connecting city traffic networks to freeways. The performance of a ramp is to some extent determined by the on-ramp lane arrangement. In this paper, our primary aim is to evaluate the performance in terms of travel time and vehicle emissions for two on-ramp lane arrangements: added lane and zip merging. We estimate the travel time and CO₂ emissions on the basis of the speed, and acceleration of vehicles in accordance with the improved comprehensive modal emission model (CMEM), and then analyse the impacts of traffic volume and heavy goods vehicles (HGVs) on travel time and emissions. The impacts of main road traffic flow on travel time and emissions for the two on-ramp lane arrangements are analysed under scenarios with traffic volumes of 800, 1 000, 1 200, 1 400, 1 600 and 1 800 vehs/h/lane. Meanwhile, the relationships between travel time, emissions and various proportions of HGVs (2%, 4%, 6%, 8% and 10%) for both on-ramp lane arrangements are evaluated as well. We eventually present emission contour charts for the two onramp lane arrangements based on the possible combinations of traffic volumes and HGV percentages.

Autonomous Vessel Scheduling

Wei Zhang, Shuai-An Wang

2020, 8(3):  391-414.  doi:10.1007/s40305-018-0218-2

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This study deals with an autonomous vessel scheduling problem when collaboration exists between port operators and an autonomous vessel company. A mixedinteger nonlinear programming model is developed, including decisions in assigning autonomous vessels to berths at each port and the optimal arrival time of each vessel at each port in an entire autonomous shipping network. This study aims to minimize the total cost of fuel consumption and the delay penalty of an autonomous vessel company. The nonlinear programming model is linearized and further solved using off-the-shelf solvers. Several experiments are conducted to test the effectiveness of the model and to draw insights for commercializing autonomous vessels. Results show that a company may speed up an autonomous vessel with short-distance voyage once fuel price decreases to gain additional benefits.

Optimization of Correspondence Times in Bus Network Zones, Modeling and Resolution by the Multi-agent Approach

Elbaz Hassane, Elhilali Alaoui Ahmed

2020, 8(3):  415-436.  doi:10.1007/s40305-020-00307-8

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Urban transportation, especially bus transportation, is an important sign of development in every city in the world. The average waiting time for passengers at correspondence stations of buses is one of the most important measures of effectiveness of bus transportation. To the best of our knowledge, the studies in the literature are about maximizing the number of synchronizations in those correspondence stations whose objective is to minimize the waiting time in the network. The classical definition of synchronization used in the literature related to a time window. In this work, we introduce a new definition of synchronization of two buses in network zones. Within this context, we present a mathematical formulation of the synchronization bus timetabling problem as a multi-objective program, where we use the new meaning for synchronization of two buses in the network zones. Since the problem is NP-hard, we adapt a multi-agent approach to solve it. Numerical experiments show that after adapting the multi-agent approach using our proposed definition, we obtain high-quality solutions compared to the classical definition.

Optimizing Locations and Scales of Emergency Warehouses Based on Damage Scenarios

Bo-Chen Wang, Miao Li, Yi Hu, Lin Huang, Shu-Min Lin

2020, 8(3):  437-456.  doi:10.1007/s40305-018-0215-5

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Choosing the locations and the capacities of emergency warehouses for the storage of relief materials is critical to the quality of services provided in the wake of a largescale emergency such as an earthquake. This paper proposes a stochastic programming model to determine disaster sites’ locations as well as their scales by considering damaged scenarios of the facility and by introducing seismic resilience to describe the ability of disaster sites to resist earthquakes. The objective of the model is to minimize fixed costs of building emergency warehouses, expected total transportation costs under uncertain demands of disaster sites and penalty costs for lack of relief materials. A local branching (LB) based solution method and a particle swarm optimization (PSO) based solution method are proposed for the problem. Extensive numerical experiments are conducted to assess the efficiency of the heuristic according to the real data of Yunnan province in China.

A Genetic Algorithm to Minimize the Makespan in a Two-Machine Cross-Docking Flow Shop Problem

Imen Hamdi, Mohamed Fadhel Tekaya

2020, 8(3):  457-476.  doi:10.1007/s40305-019-00277-6

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We consider the problem of two-machine cross-docking flow shop scheduling where each job on the second machine cannot be processed unless a job or a set of jobs have been completed on the first machine. The aim is to find a feasible schedule that minimizes the makespan. As the problem is shown to be strongly NP-hard, we propose a genetic algorithm to solve small and large size problems. We test different types for each genetic operator where new ideas are introduced, which leads to propose six versions of the genetic algorithm. We then evaluate their effectiveness through an extensive computational experiments by using many instances generated randomly and by determining the percentage deviation from a lower bound from the literature.

Flight-Based Congestion Pricing Considering Equilibrium Flights in Airport Airside

Bao-Cheng Zhang

2020, 8(3):  477-491.  doi:10.1007/s40305-020-00306-9

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Most of the previous works ignore the fact that equilibrium flights in self-profit maximization scenario are totally different from that in joint profit (social welfare) maximization scenario and take price difference (flight fare difference) between the two scenarios as congestion price, which is a passenger-based method. Most of all, the function of congestion pricing is to alleviate congestion by making airlines reduce flights at peak time. Therefore, the equilibrium flights under self-profit maximization should be the same as the ones under joint profit maximization after congestion prices are tolled. Flight-based congestion pricing method is provided in our paper. The analysis suggests no role for congestion pricing when total real flight production of all airlines is less than the equilibrium flights under joint profit maximization scenario. Otherwise, congestion tolls should be levied to all airlines. Furthermore, congestion price can be determined by solving the corresponding equations system.

Collaborative Optimization of Dock Door Assignment and Vehicle Scheduling in Cross-Docking

Yue Li, Rui-Yun Tang, Li-Wen MuRong, Qian Sun

2020, 8(3):  493-514.  doi:10.1007/s40305-019-00266-9

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Cross-docking is a logistic strategy that can transport goods directly from suppliers or manufacturers to retailers or customers. In daily life, the requirements for timeliness of goods distribution have been continuously improved. Cross-docking can realize the rapid transshipment of goods and improve the process efficiency of distribution greatly. Meanwhile, during the cross-docking process, goods are deposited in the temporary storage area, which reduces the storage cost. This paper focuses on the analysis of reasonable vehicle scheduling and dock door allocation problems in cross-docking. The goal is to minimize the working time of cross-docks by the research on this combinatorial optimization problem. This paper proposes the genetic algorithm (GA) and the hybrid particle swarm optimization to solve the three-scale (small, medium and large) cross-docks. Optimal completion time, average completion time and average solution time are considered as factors to evaluate the efficiency of two algorithms on three scales. And then the concept of mixed-mode dock door is introduced. GA is used to conduct numerical experiments with mixed dock doors on different scales. Finally, by comparing the utilization rate of mixed dock doors, we can analyze the influence of mixed dock door on vehicles’ waiting time.

Optimizing Distribution Route of Convenience Vegetable Stores Considering Transit Nodes

Pu Li, Hong-Jie Lan, You-Hua Chen

2020, 8(3):  515-531.  doi:10.1007/s40305-020-00319-4

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Convenience vegetable stores are distributed in various districts of the city, which is difficult to distribute, mainly reflected in the high cost of distribution and transportation. In order to solve this problem, combining with the characteristics of convenience vegetable stores and urban transportation, an optimization model of distribution route considering transit nodes is established. The model takes into account both soft time window and hard time window. Soft time window is used to calculate the cost increase caused by an urban traffic jam. Hard time window is the unified service time of convenience vegetable stores, and the cost of transit damage is considered to make the model more realistic. The genetic algorithm is used to solve the model with a onestage solution method. The effectiveness and feasibility of the model and algorithm are verified by an example. The effectiveness of the proposed algorithm is verified by comparing the optimal solutions in the case of setting up transit and not setting up transit. The result shows that when the number of convenience vegetable stores is large, the establishment of transit can reduce the overall transportation cost. Quantitative analysis shows that with the further increase in convenience vegetable stores in cities, the distribution of convenience vegetable stores can be improved by planning scientific path and by increasing transit nodes.