scholarly journals The Optimal Dispatch of Traffic and Patrol Police Service Platforms

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Ke Quan Zhao ◽  
Li Luo ◽  
Yuan Mei Xia
Keyword(s):  
Traffic Congestion ◽  
Numerical Experiments ◽  
Programming Model ◽  
Police Service ◽  
Optimal Dispatch ◽  
Minmax Programming

The main goal of this paper is to present a minmax programming model for the optimal dispatch of Traffic and Patrol Police Service Platforms with single traffic congestion. The objective is to minimize the longest time of the dispatch for Traffic and Patrol Police Service Platforms. Some numerical experiments are carried out, and the optimal project is given.

scholarly journals Integrated Harvest and Farm-to-Door Distribution Scheduling with Postharvest Quality Deterioration for Vegetable Online Retailing

Agronomy ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. 724
Author(s):  
Yiping Jiang ◽  
Bei Bian ◽  
Lingling Li
Keyword(s):  
Genetic Algorithm ◽  
Numerical Experiments ◽  
Programming Model ◽  
Time Windows ◽  
Sensitivity Analyses ◽  
Postharvest Quality ◽  
Online Retailing ◽  
Quality Deterioration ◽  
Distribution Scheduling ◽  
Proposed Model

With the rise of vegetable online retailing in recent years, the fulfillment of vegetable online orders has been receiving more and more attention. This paper addresses an integrated optimization model for harvest and farm-to-door distribution scheduling for vegetable online retailing. Firstly, we capture the perishable property of vegetables, and model it as a quadratic postharvest quality deterioration function. Then, we incorporate the postharvest quality deterioration function into the integrated harvest and farm-to-door distribution scheduling and formulate it as a quadratic vehicle routing programming model with time windows. Next, we propose a genetic algorithm with adaptive operators (GAAO) to solve the model. Finally, we carry out numerical experiments to verify the performance of the proposed model and algorithm, and report the results of numerical experiments and sensitivity analyses.

scholarly journals Research on Optimization and Design of Sustainable Urban Underground Logistics Network Framework

2020 ◽  
Vol 12 (21) ◽  
pp. 9147
Author(s):  
Hairui Wei ◽  
Anlin Li ◽  
Nana Jia
Keyword(s):  
Hybrid Method ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Programming Model ◽  
Mixed Integer ◽  
Set Cover ◽  
Exhaust Emission ◽  
Logistics Network ◽  
Design And Optimization ◽  
Fuzzy Clustering Method

As a new mode of transportation, the underground logistics system (ULS) has become one of the solutions to the problems of environmental pollution and traffic congestion. Considering the environmental and economic factors in urban logistics, this paper conducts comprehensive design and optimization research on the network nodes and passages of urban underground logistics and proposes a relatively complete framework for a sustainable underground logistics network. A hybrid method is proposed, which includes the set cover model used to perform the first location of urban underground logistics nodes, the fuzzy clustering method applied to classify the located logistics nodes into the first-level and second-level nodes considering the congestion in different urban areas of the city and a mixed integer programming model proposed to optimize and design the underground logistics passage to find optimal passage parameters at every underground logistics node. Based on the above hybrid method, a sustainable underground logistics network framework including all-levels logistics nodes and passages is formed, with a subdistrict of Nanjing as a case study. The discussion of results shows that this underground logistics network framework proposal is very effective in reducing logistics time cost, exhaust emission and congestion cost. It provides support for decisions in the design and development of urban sustainable underground logistics networks.

scholarly journals Applying a Model for Trip Assignment and Dynamic Routing of Automated Taxis with Congestion: System Performance in the City of Delft, The Netherlands

2018 ◽  
Vol 2672 (8) ◽  
pp. 588-598 ◽  
Author(s):  
Xiao Liang ◽  
Gonçalo Homem de Almeida Correia ◽  
Bart van Arem
Keyword(s):  
The Netherlands ◽  
Real Time ◽  
Traffic Congestion ◽  
Programming Model ◽  
Profit Maximization ◽  
The Real ◽  
Real Size ◽  
The Impact ◽  
The City

This paper proposes a method of assigning trips to automated taxis (ATs) and designing the routes of those vehicles in an urban road network, and also considering the traffic congestion caused by this dynamic responsive service. The system is envisioned to provide a seamless door-to-door service within a city area for all passenger origins and destinations. An integer programming model is proposed to define the routing of the vehicles according to a profit maximization function, depending on the dynamic travel times, which varies with the ATs’ flow. This will be especially important when the number of automated vehicles (AVs) circulating on the roads is high enough that their routing will cause delays. This system should be able to serve not only the reserved travel requests, but also some real-time requests. A rolling horizon scheme is used to divide one day into several periods in which both the real-time and the booked demand will be considered together. The model was applied to the real size case study city of Delft, the Netherlands. The results allow assessing of the impact of the ATs movements on traffic congestion and the profitability of the system. From this case-study, it is possible to conclude that taking into account the effect of the vehicle flows on travel time leads to changes in the system profit, the satisfied percentage and the driving distance of the vehicles, which highlights the importance of this type of model in the assessment of the operational effects of ATs in the future.

scholarly journals Simultaneous Optimization of Road Tolls and Tradable Credits in Public-private Mixed Networks

2017 ◽  
Vol 29 (6) ◽  
pp. 603-611 ◽  
Author(s):  
Nan Jiang ◽  
Xiaoning Zhang ◽  
Hua Wang
Keyword(s):  
Traffic Congestion ◽  
Programming Model ◽  
User Equilibrium ◽  
Simultaneous Optimization ◽  
Management Policy ◽  
Mixed Integer ◽  
Private Company ◽  
Mixed Integer Linear Program ◽  
The Government ◽  
Tradable Credits

This paper investigates a hybrid management policy of road tolls and tradable credits in mixed road networks with both public and private roads. In the public sub-network, a tradable credit scheme is applied to mitigate traffic congestion. In the private sub-network, tolls are collected by the private company, but the toll levels and toll locations are determined by the government. The purpose of toll charge is two-fold: on the one hand, the government uses it as a tool for mitigating congestion; on the other hand, a threshold of revenue should be guaranteed for the profitability of the private company. A bi-level programming model is formulated to minimize the total travel time in the network by taking into account the user equilibrium travel behaviour and the revenue requirement of private firms. To obtain a  global optimum solution, the bi-level model is transformed into an equivalent single-level mixed integer linear program that can be easily solved with commercial software. Numerical examples are provided to demonstrate the effectiveness of the developed model and the efficiency of the proposed algorithm. It is shown that the mixed management schemes can achieve favourable targets, namely, joint implementation of road tolls and tradable credits can effectively mitigate traffic congestion and meanwhile maintain reasonable revenue for the private company.

User and Operator Perspectives in Public Transport Timetable Synchronization Design

2017 ◽  
Vol 2667 (1) ◽  
pp. 154-163
Author(s):  
Tao Liu ◽  
Avishai (Avi) Ceder
Keyword(s):  
Public Transport ◽  
Traffic Congestion ◽  
Large Scale ◽  
Systems Approach ◽  
Programming Model ◽  
Efficient Solutions ◽  
Linear Constraints ◽  
Nonlinear Integer Programming ◽  
Modeling Framework ◽  
Objective Model

Increased traffic congestion and the adverse environmental effect of private cars have resulted in an increasingly pressing need for an integrated public transport (PT) system that is more attractive than private car use. The intelligent PT timetable synchronization design is one way to improve the integration and service quality of a PT system with increased connectivity, synchronization, and attractiveness toward far more user-oriented, system-optimal, smart, and sustainable travel. This paper proposes a new multicriteria optimization modeling framework with a systems approach for the PT timetable synchronization design problem. A new bi-objective model is proposed; it takes PT user and operator interests into account. The nature of the overall mathematical formulations of the new model is bi-objective nonlinear integer programming with linear constraints. On the basis of the characteristics of the model, a novel deficit function (DF)–based sequential search method is proposed to solve the problem so as to obtain Pareto-efficient solutions. The visual nature of the proposed DF and the two-dimensional fleet-cost space graphical techniques can facilitate the decision-making process of PT schedulers for finding a desired solution. Numerical results from a small PT network demonstrate that the proposed mathematical programming model and solution method are effective in practice and have the potential to be applied in large-scale and realistic networks.

scholarly journals Integrated Optimization on Assortment Packing and Collaborative Shipping for Fashion Clothing

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Qianying Wang ◽  
Yiping Jiang ◽  
Yang Liu
Keyword(s):  
Numerical Experiments ◽  
Optimization Problem ◽  
Programming Model ◽  
Social Resources ◽  
Mixed Integer ◽  
Integrated Optimization ◽  
Proposed Model ◽  
Integer Nonlinear Programming ◽  
Nonlinear Programming Model ◽  
Effectiveness And Efficiency

With the diversification of customer’s demand and the shortage of social resources, meeting diverse requirements of customers and reducing logistics costs have attracted great attention in logistics area. In this paper, we address an integrated optimization problem that combines fashion clothing assortment packing with collaborative shipping simultaneously. We formulate this problem as a mixed integer nonlinear programming model (MINLP) and then convert the proposed model into a simplified model. We use LINGO 11.0 to solve the transformed model. Numerical experiments have been conducted to verify the effectiveness and efficiency of the proposed model, and the numerical results show that the proposed model is beneficial to the fashion clothing assortment packing and collaborative shipping planning.

Research on the Modeling of Tugboat Assignment Problem in Container Terminal

2012 ◽  
Vol 433-440 ◽  
pp. 1957-1961 ◽  
Author(s):  
Su Wang ◽  
Iko Kaku ◽  
Guo Yue Chen ◽  
Min Zhu
Keyword(s):  
Assignment Problem ◽  
Numerical Experiments ◽  
Solution Method ◽  
Programming Model ◽  
Container Terminal ◽  
Optimal Solution ◽  
Turnaround Time ◽  
Mixed Integer ◽  
Service Capacity ◽  
Decision Making Problem

Tugboat is one kind of important equipment in container terminal to help ships for docking or leaving the berth. Tugboat assignment operation is one of the most important decision making problem because it has an important effect on the turnaround time of ships. In this paper, a mixed-integer programming model combined with scheduling rule is formulated for the Tugboat Assignment Problem (TAP). Then a solution method is provided to obtain the optimal solution of TAP problem. Finally, numerical experiments are executed to illustrate the utility of the model and to analyze the effects of the number and service capacity of tugboats on the turnaround time of ships.

scholarly journals Berth Allocation and Quay Crane Assignment Under Uncertainties

2020 ◽  
Author(s):  
Caimao Tan ◽  
Junliang He ◽  
Yuancai Wang
Keyword(s):  
Stochastic Programming ◽  
Numerical Experiments ◽  
Programming Model ◽  
Berth Allocation ◽  
Berth Allocation Problem ◽  
Operations Planning ◽  
Proposed Model ◽  
Departure Time ◽  
Stochastic Programming Model ◽  
Quay Crane Assignment

The integration of berth allocation problem (BAP) and quay crane assignment problem (QCAP) is an cardinal seaside operations planning, which is susceptible to uncertainties, e.g. uncertain vessels arrival and maritime market. This paper addresses the integrated optimization of BAP and QCAP under uncertainties. A stochastic programming model is formulated for minimizing the waiting time and delay departure time of vessels. Besides, numerical experiments and scenario analysis are conducted to validate the effectiveness of the proposed model.

scholarly journals Scheduling Jobs with Maintenance Subject to Load-Dependent Duration on a Single Machine

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Yawei Qi ◽  
Long Wan ◽  
Zhigang Yan
Keyword(s):  
Integer Programming ◽  
Single Machine ◽  
Numerical Experiments ◽  
Heuristic Algorithms ◽  
Programming Model ◽  
Scheduling Problem ◽  
Np Hard ◽  
Ordinary Sense ◽  
Starting Time ◽  
Special Case

This paper investigates a scheduling problem on a single machine with maintenance, in which the starting time of the maintenance is given in advance but its duration depends on the load of the machine before the maintenance. The goal is to minimize the makespan. We formulate it as an integer programming model and show that it is NP-hard in the ordinary sense. Then, we propose an FPTAS and point out that a special case is polynomial solvable. Finally, we design fast heuristic algorithms to solve the scheduling problem. Numerical experiments are implemented to evaluate the performance of the proposed heuristic algorithms. The results show the proposed heuristic algorithms are effective.

scholarly journals Heuristic Algorithms for MapReduce Scheduling Problem with Open-Map Task and Series-Reduce Tasks

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Feifeng Zheng ◽  
Zhaojie Wang ◽  
Yinfeng Xu ◽  
Ming Liu
Keyword(s):  
Numerical Experiments ◽  
Simulated Annealing Algorithm ◽  
Heuristic Algorithms ◽  
Programming Model ◽  
Mixed Integer ◽  
Scheduling Problem ◽  
Scheduling Model ◽  
Open Map ◽  
Annealing Algorithm ◽  
Mapreduce Scheduling

Based on the classical MapReduce concept, we propose an extended MapReduce scheduling model. In the extended MapReduce scheduling problem, we assumed that each job contains an open-map task (the map task can be divided into multiple unparallel operations) and series-reduce tasks (each reduce task consists of only one operation). Different from the classical MapReduce scheduling problem, we also assume that all the operations cannot be processed in parallel, and the machine settings are unrelated machines. For solving the extended MapReduce scheduling problem, we establish a mixed-integer programming model with the minimum makespan as the objective function. We then propose a genetic algorithm, a simulated annealing algorithm, and an L-F algorithm to solve this problem. Numerical experiments show that L-F algorithm has better performance in solving this problem.

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