scholarly journals Drone-Based Parcel Delivery Using the Rooftops of City Buildings: Model and Solution

2020 ◽  
Vol 10 (12) ◽  
pp. 4362 ◽  
Author(s):  
Junsu Kim ◽  
Hongbin Moon ◽  
Hosang Jung
Keyword(s):  
Urban Areas ◽  
Programming Model ◽  
Computation Time ◽  
Intelligent Transportation ◽  
Mixed Integer ◽  
Operation Planning ◽  
Logistics System ◽  
Proposed Model ◽  
Optimality Gap ◽  
Good Operation

In general, the demand for delivery cannot be fulfilled efficiently due to the excessive traffic in dense urban areas. Therefore, many innovative concepts for intelligent transportation of freight have recently been developed. One of these concepts relies on drone-based parcel delivery using rooftops of city buildings. To apply drone logistics system in cities, the operation design should be adequately prepared. In this regard, a mixed integer programming model for drone operation planning and a heuristic based on block stacking are newly proposed to provide solutions. Additionally, numerical experiments with three different problem sizes are conducted to check the feasibility of the proposed model and to assess the performance of the proposed heuristic. The experimental results show that the proposed model seems to be viable and that the developed heuristic provides very good operation plans in terms of the optimality gap and the computation time.

scholarly journals Network Planning Method for Capacitated Metro-Based Underground Logistics System

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Jianjun Dong ◽  
Wanjie Hu ◽  
Shen Yan ◽  
Rui Ren ◽  
Xiaojing Zhao
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Programming Model ◽  
Evaluation Model ◽  
Network Planning ◽  
Exact Algorithm ◽  
Planning Method ◽  
Mixed Integer ◽  
Logistics System ◽  
Metro System

Underground logistics system (ULS) tends to alleviate traffic congestion, increase city logistics efficiency, mitigate the negative effects of traditional logistics processes, and improve the sustainability of urban areas. However, the relatively high cost and risk of underground construction are serious obstacles to implementing ULS. Integrating ULS into modern metro system (M-ULS) is considered to be feasible and efficient to solve this problem. This paper aims at developing a metro system-based ULS network planning method. First, an evaluation model of underground freight volume was proposed considering service capacity, freight flow, and regional accessibility. Second, a set of mixed integer programming model was developed to solve the problem of optimal nodes’ location-allocation (LAP) in the network. Then, a hybrid algorithm was designed with a combination of E-TOPSIS, exact algorithm, and heuristic algorithm. Finally, two lines of Nanjing Metro were selected as a case to validate the proposed planning method. The results showed that the new system can significantly reduce the construction costs of ULS and alleviate traffic congestion. Moreover, the potential of metro stations and underground tunnels can be fully exploited to achieve higher logistics benefits.

Quality indicator of the smart city transportation and logistics system

2020 ◽  
Vol 19 (11) ◽  
pp. 2116-2135
Author(s):  
G.V. Savin
Keyword(s):  
Intelligent Transportation Systems ◽  
Smart City ◽  
Urban Areas ◽  
Human Life ◽  
Life Quality ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Logistics System ◽  
Organization And Management

Subject. The article considers functioning and development of process flows of transportation and logistics system of a smart city. Objectives. The study identifies factors and dependencies of the quality of human life on the organization and management of stream processes. Methods. I perform a comparative analysis of previous studies, taking into account the uniquely designed results, and the econometric analysis. Results. The study builds multiple regression models that are associated with stream processes, highlights interdependent indicators of temporary traffic and pollution that affect the indicator of life quality. However, the identified congestion indicator enables to predict the time spent in traffic jams per year for all participants of stream processes. Conclusions. The introduction of modern intelligent transportation systems as a component of the transportation and logistics system of a smart city does not fully solve the problems of congestion in cities at the current rate of urbanization and motorization. A viable solution is to develop cooperative and autonomous intelligent transportation systems based on the logistics approach. This will ensure control over congestion, the reduction of which will contribute to improving the life quality of people in urban areas.

scholarly journals Allocation and Scheduling of Handling Resources in the Railway Container Terminal Based on Crossing Crane Area

2021 ◽  
Vol 13 (3) ◽  
pp. 1190
Author(s):  
Gang Ren ◽  
Xiaohan Wang ◽  
Jiaxin Cai ◽  
Shujuan Guo
Keyword(s):  
Programming Model ◽  
Container Terminal ◽  
Simultaneous Optimization ◽  
Mixed Integer ◽  
Gantry Crane ◽  
Optimization Scheme ◽  
Long Distance ◽  
Proposed Model ◽  
Hybrid Heuristic Algorithm ◽  
Searching Ability

The integrated allocation and scheduling of handling resources are crucial problems in the railway container terminal (RCT). We investigate the integrated optimization problem for handling resources of the crane area, dual-gantry crane (GC), and internal trucks (ITs). A creative handling scheme is proposed to reduce the long-distance, full-loaded movement of GCs by making use of the advantages of ITs. Based on this scheme, we propose a flexible crossing crane area to balance the workload of dual-GC. Decomposing the integrated problem into four sub-problems, a multi-objective mixed-integer programming model (MIP) is developed. By analyzing the characteristic of the integrated problem, a three-layer hybrid heuristic algorithm (TLHHA) incorporating heuristic rule (HR), elite co-evolution genetic algorithm (ECEGA), greedy rule (GR), and simulated annealing (SA) is designed for solving the problem. Numerical experiments were conducted to verify the effectiveness of the proposed model and algorithm. The results show that the proposed algorithm has excellent searching ability, and the simultaneous optimization scheme could ensure the requirements for efficiency, effectiveness, and energy-saving, as well as the balance rate of dual-GC.

scholarly journals An Optimized Mathematical Model for Items Supplies Planning of a Logistic System

2016 ◽  
Vol 10 (10) ◽  
pp. 133
Author(s):  
Mohammad Ali Nasiri Khalili ◽  
Mostafa Kafaei Razavi ◽  
Morteza Kafaee Razavi
Keyword(s):  
Mathematical Model ◽  
Mixed Integer ◽  
Logistics System ◽  
Proposed Model ◽  
Multiple Objective Decision Making ◽  
System Requirements ◽  
Purchasing Logistics ◽  
The Cost ◽  
The Mathematical Model ◽  
First Time

Items supplies planning of a logistic system is one of the major issue in operations research. In this article the aim is to determine how much of each item per month from each supplier logistics system requirements must be provided. To do this, a novel multi objective mixed integer programming mathematical model is offered for the first time. Since in logistics system, delivery on time is very important, the first objective is minimization of time in delivery on time costs (including lack and maintenance costs) and the cost of purchasing logistics system. The second objective function is minimization of the transportation supplier costs. Solving the mathematical model shows how to use the Multiple Objective Decision Making (MODM) can provide the ensuring policy and transportation logistics needed items. This model is solved with CPLEX and computational results show the effectiveness of the proposed model.

Cuckoo optimization algorithm in reverse logistics: A network design for COVID-19 waste management

2021 ◽  
pp. 0734242X2110039
Author(s):  
Elham Shadkam
Keyword(s):  
Waste Management ◽  
Network Design ◽  
Optimization Algorithm ◽  
Reverse Logistics ◽  
Heuristic Algorithms ◽  
Programming Model ◽  
Fixed Costs ◽  
Logistics System ◽  
Cuckoo Optimization Algorithm ◽  
Proposed Model

Today, reverse logistics (RL) is one of the main activities of supply chain management that covers all physical activities associated with return products (such as collection, recovery, recycling and destruction). In this regard, the designing and proper implementation of RL, in addition to increasing the level of customer satisfaction, reduces inventory and transportation costs. In this paper, in order to minimize the costs associated with fixed costs, material flow costs, and the costs of building potential centres, a complex integer linear programming model for an integrated direct logistics and RL network design is presented. Due to the outbreak of the ongoing global coronavirus pandemic (COVID-19) at the beginning of 2020 and the consequent increase in medical waste, the need for an inverse logistics system to manage waste is strongly felt. Also, due to the worldwide vaccination in the near future, this waste will increase even more and careful management must be done in this regard. For this purpose, the proposed RL model in the field of COVID-19 waste management and especially vaccine waste has been designed. The network consists of three parts – factory, consumers’ and recycling centres – each of which has different sub-parts. Finally, the proposed model is solved using the cuckoo optimization algorithm, which is one of the newest and most powerful meta-heuristic algorithms, and the computational results are presented along with its sensitivity analysis.

A Multi-Period Evacuation Vehicle Routing Problem Model

2014 ◽  
Vol 931-932 ◽  
pp. 578-582
Author(s):  
Sunarin Chanta ◽  
Ornurai Sangsawang
Keyword(s):  
Vehicle Routing ◽  
Public Transportation ◽  
Vehicle Routing Problem ◽  
Programming Model ◽  
High Water ◽  
Mixed Integer ◽  
Routing Problem ◽  
Problem Model ◽  
Proposed Model ◽  
Evacuation Routing

In this paper, we proposed an optimization model that addresses the evacuation routing problem for flood disaster when evacuees trying to move from affected areas to safe places using public transportation. A focus is on the situation of evacuating during high water level when special high vehicles are needed. The objective is to minimize the total traveled distance through evacuation periods where a limited number of vehicles is given. We formulated the problem as a mixed integer programming model based on the capacitated vehicle routing problem with multiple evcuation periods where demand changing by the time. The proposed model has been tested on a real-world case study affected by the severe flooding in Thailand, 2011.

scholarly journals A Synchronous Optimization Model for Multiship Shuttle Tanker Fleet Design and Scheduling Considering Hard Time Window Constraint

2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Zhenfeng Jiang ◽  
Dongxu Chen ◽  
Zhongzhen Yang
Keyword(s):  
Time Window ◽  
Programming Model ◽  
Transportation Cost ◽  
Exact Algorithm ◽  
Mixed Integer ◽  
Routing Problem ◽  
Hard Time ◽  
Proposed Model ◽  
Total Transportation Cost ◽  
Time Window Constraints

A Synchronous Optimization for Multiship Shuttle Tanker Fleet Design and Scheduling is solved in the context of development of floating production storage and offloading device (FPSO). In this paper, the shuttle tanker fleet scheduling problem is considered as a vehicle routing problem with hard time window constraints. A mixed integer programming model aiming at minimizing total transportation cost is proposed to model this problem. To solve this model, we propose an exact algorithm based on the column generation and perform numerical experiments. The experiment results show that the proposed model and algorithm can effectively solve the problem.

scholarly journals Soft Computing Methodology to Optimize the Integrated Dynamic Models of Cellular Manufacturing Systems in a Robust Environment

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Amir-Mohammad Golmohammadi ◽  
Hasan Rasay ◽  
Zaynab Akhoundpour Amiri ◽  
Maryam Solgi ◽  
Negar Balajeh
Keyword(s):  
Machine Learning ◽  
Programming Model ◽  
Facility Layout ◽  
Cell Formation ◽  
Layout Design ◽  
Metaheuristic Algorithms ◽  
Sensitivity Analyses ◽  
Mixed Integer ◽  
Facility Layout Design ◽  
Proposed Model

Machine learning, neural networks, and metaheuristic algorithms are relatively new subjects, closely related to each other: learning is somehow an intrinsic part of all of them. On the other hand, cell formation (CF) and facility layout design are the two fundamental steps in the CMS implementation. To get a successful CMS design, addressing the interrelated decisions simultaneously is important. In this article, a new nonlinear mixed-integer programming model is presented which comprehensively considers solving the integrated dynamic cell formation and inter/intracell layouts in continuous space. In the proposed model, cells are configured in flexible shapes during the planning horizon considering cell capacity in each period. This study considers the exact information about facility layout design and material handling cost. The proposed model is an NP-hard mixed-integer nonlinear programming model. To optimize the proposed problem, first, three metaheuristic algorithms, that is, Genetic Algorithm (GA), Keshtel Algorithm (KA), and Red Deer Algorithm (RDA), are employed. Then, to further improve the quality of the solutions, using machine learning approaches and combining the results of the aforementioned algorithms, a new metaheuristic algorithm is proposed. Numerical examples, sensitivity analyses, and comparisons of the performances of the algorithms are conducted.

scholarly journals Local Blood Supply Chain Optimization: A Case Study

2020 ◽  
Vol 18 (4) ◽  
Author(s):  
Reza Babazadeh ◽  
Ali Sabbaghnia ◽  
Fatemeh Shafipour
Keyword(s):  
Supply Chain ◽  
Blood Supply ◽  
Blood Donation ◽  
Programming Model ◽  
Human Life ◽  
Mixed Integer ◽  
Model Parameters ◽  
Supply Chain Optimization ◽  
Blood Supply Chain ◽  
Proposed Model

: Blood and its products play an undeniable role in human life. In recent years, although both academics and practitioners have investigated blood-related problems, further enhancement is still warranted. In this study, a mixed-integer linear programming model was proposed for local blood supply chain management. A supply network, including temporary and fixed blood donation facilities, blood banks, and blood processing centers, was designed regarding the deteriorating nature of blood. The proposed model was applied in a real case in Urmia, Iran. The numerical results and sensitivity analysis of the key model parameters ensured the applicability of the proposed model.

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.

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