scholarly journals Design of a Support System for Complicated Logistics Location Integrating Big Data

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Yusi Cheng ◽  
Xinwei Pan
Keyword(s):  
Big Data ◽  
Support System ◽  
Traffic Congestion ◽  
Set Covering ◽  
Ant Colony Optimization Algorithm ◽  
Construction Costs ◽  
Logistics System ◽  
Logistics Network ◽  
Analysis Technique ◽  
Covering Model

Logistics location is an important component of logistics planning that affects traffic pressure and vehicle emissions. To date, there has not been an adequate study of the integration of big data into the location for a complicated logistics system. This study developed a decision support system that can address location problems for complicated logistics systems, e.g., a multilevel urban underground logistics system (ULS), using logistics big data. First, information needed in the logistics location, such as the traffic performance index (TPI) and the origin/destination (OD) matrix, was collected and calculated using a big data platform, and this information was digitized and represented based on a geographic information system (GIS) tool. Second, a two-stage location model for a ULS was designed to balance the construction costs and traffic congestion. The first stage is establishing a set-covering model to identify optimum locations for secondary hubs based on the ant colony optimization algorithm, and the second stage is clustering of the secondary hubs to determine locations for primary hubs using the iterative self-organizing data analysis technique algorithm (ISODATA). Finally, the Xianlin district of Nanjing, China, was chosen as a case study to validate the effectiveness of the proposed system. The system can be used to facilitate logistics network planning and to promote the application of big data in logistics.

scholarly journals A Novel Hybrid Algorithm for Multiobjective Location-Allocation Problem in Emergency Logistics

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Hongrui Chu ◽  
Yahong Chen
Keyword(s):  
Optimization Model ◽  
Complex Model ◽  
Theory And Practice ◽  
Logistics System ◽  
Logistics Network ◽  
Location Allocation ◽  
Emergency Logistics ◽  
Ga Algorithm ◽  
Relief Distribution ◽  
Deprivation Costs

Increased frequency of disasters keeps reminding us of the importance of effective resource distribution in postdisaster. To reduce the suffering of victims, this paper focuses on how to establish an effective emergency logistics system. We first propose a multiobjective optimization model in which the location and allocation decisions are made for a three-level logistics network. Three objectives, deprivation costs, unsatisfied demand costs, and logistics cost, are adopted in the proposed optimization model. Several cardinality and flow balance constraints are considered simultaneously. Then, we design a novel effective IFA-GA algorithm by combining the firefly algorithm and genetic algorithm to solve this complex model effectively. Furthermore, three schemes are proposed to improve the effectiveness of the IFA-GA algorithm. Finally, the numerical results provide several insights on the theory and practice of relief distribution, which also illustrate the validity of the proposed solution algorithm.

scholarly journals Set Covering Model in Solving Multiple Cutting Stock Problem

2020 ◽  
Vol 5 (4) ◽  
pp. 121
Author(s):  
Sisca Octarina ◽  
Devi Gusmalia Juita ◽  
Ning Eliyati ◽  
Putra Bahtera Jaya Bangun
Keyword(s):  
Column Generation ◽  
Pattern Generation ◽  
Cutting Stock Problem ◽  
Set Covering ◽  
Cutting Stock ◽  
Second Stage ◽  
Generation Technique ◽  
Cutting Pattern ◽  
Covering Model

Cutting Stock Problem (CSP) is the determination of how to cut stocks into items with certain cutting rules. A diverse set of stocks is called multiple stock CSP. This study used Pattern Generation (PG) algorithm to determine cutting pattern, then formulated it into a Gilmore and Gomory model and solved by using Column Generation Technique (CGT). Set Covering model was generated from Gilmore and Gomory model. Based on the results, selected cutting patterns in the first stage can be used in the second stage. The combination of patterns generated from Gilmore and Gomory model showed that the use of stocks was more effective than Set Covering model.  

scholarly journals Analyzing the Issue of On-street Parking in Commercial Areas: A Case Study of the City of Hyderabad, Pakistan

2018 ◽  
Vol 01 (02) ◽  
pp. 01-09
Author(s):  
Baig Farrukh ◽  
Sahito Noman ◽  
Bano Arsla ◽  
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Survey Methodology ◽  
Greenhouse Gas Emission ◽  
Central Business District ◽  
Rapid Urbanization ◽  
Analysis Technique ◽  
Business District ◽  
Public Views ◽  
The City

In developing countries, rapid urbanization has created an enormous pressure on land use, infrastructure and transportation. The fast growing ratio of motorized vehicles in urban areas is the main cause of environmental degradation. Almost 80% of the greenhouse gas emission is from vehicles in cities. In the city centers, on-street parking is considered the major cause of traffic congestion. The aim of this study was to evaluate the problems of on-street parking and disorderly parking at Central Business District (CBD) of Hyderabad city. The field survey methodology was adopted to perceive the current traffic problems in the city center and traffic count survey was carried out in both peak and off hours. The data was analyzed using descriptive statistics frequency analysis technique with the help of Statistical Package for the Social Sciences (SPSS). The findings revealed that increasing number of vehicles, on-street parking, improper parking, encroachment, inadequate parking space and poor condition of roads are the main causes of traffic congestion. The study bridges up the research gap of determining public views about on-street parking challenges in the context of Hyderabad, Pakistan and provides statistical results which may equally be adapted by policy makers and transportation planners in order to improve the traffic situation.

scholarly journals Adaptability of the Logistics System in National Economic Mobilization Based on Blocking Flow Theory

2014 ◽  
Vol 2014 ◽  
pp. 1-6
Author(s):  
Xiangyuan Jing ◽  
Qingmei Tan ◽  
Liusan Wu ◽  
Xiaohui Li
Keyword(s):  
Traffic Congestion ◽  
Negative Impact ◽  
Heavy Traffic ◽  
Human Beings ◽  
Rescue Operation ◽  
Logistics System ◽  
Great Loss ◽  
National Economic ◽  
Flow Theories ◽  
Optimum Model

In the process of national economic mobilization, the logistics system usually suffers from negative impact and/or threats of such emergency events as wars and accidents, which implies that adaptability of the logistics system directly determines realization of economic mobilization. And where the real-time rescue operation is concerned, heavy traffic congestion is likely to cause a great loss of or damage to human beings and their properties. To deal with this situation, this article constructs a blocking-resistance optimum model and an optimum restructuring model based on blocking flow theories, of which both are illustrated by numerical cases and compared in characteristics and application. The design of these two models is expected to eliminate or alleviate the congestion situation occurring in the logistics system, thus effectively enhancing its adaptability in the national economic mobilization process.

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