scholarly journals A Stochastic Programming Approach for Resilient Hub Location in Power Projection Network considering Random Hub Failures

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Xu-Tao Zhang ◽  
Hai-Ling Bi ◽  
Yun Wang
Keyword(s):  
Stochastic Programming ◽  
Programming Model ◽  
Programming Approach ◽  
Hub Location ◽  
Hub Location Problem ◽  
Power Projection ◽  
Critical Facilities ◽  
Resilient Networks ◽  
The Impact ◽  
Projection Network

Hubs are critical facilities in the power projection network. Due to the uncertainty factors such as terrorism threats, severe weather, and natural disasters, hub facilities may be disrupted randomly, which could lead to excessive cost or loss in practice. One of the most effective ways to withstand and reduce the impact of disruptions is designing more resilient networks. In this paper, a stochastic programming model is employed for the hub location problem in the presence of random hub failures. A heuristic algorithm based on Monte Carlo method and tabu search is put forward to solve the model. The proposed approach is more general if there are numbers of hubs that would fail even with different failure probability. Compared with the benchmark model, the model which takes the factor of stochastic failure of hubs into account can give a more resilient power projection network.

scholarly journals A Biobjective and Trilevel Programming Model for Hub Location Problem in Design of a Resilient Power Projection Network

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Hai-Ling Bi ◽  
Kai Kang ◽  
Xu-Tao Zhang
Keyword(s):  
Programming Model ◽  
Multiple Criteria Decision Making ◽  
Complex Model ◽  
Hub Location ◽  
Hub Location Problem ◽  
Worst Case ◽  
Power Projection ◽  
Network Cost ◽  
The Cost ◽  
Projection Network

Hubs disruptions are taken into account in design of a resilient power projection network. The problem is tackled from a multiple criteria decision-making (MCDM) perspective. Not only the network cost in normal state is considered, but also the cost in the worst-case situation is taken into account. A biobjective and trilevel integer programming model is proposed using game theory. Moreover, we develop a metaheuristic based on tabu search and shortest path algorithm for the resolution of the complex model. Computational example indicates that making tradeoffs between the performances of the network in different situations is helpful for designing a resilient network.

scholarly journals Location of regional and international hub ports in liner shipping

2017 ◽  
Vol 2 (2) ◽  
pp. 114-125 ◽  
Author(s):  
Jianfeng Zheng ◽  
Cong Fu ◽  
Haibo Kuang
Keyword(s):  
Design Methodology ◽  
Location Problem ◽  
Programming Model ◽  
Liner Shipping ◽  
Mixed Integer ◽  
Eastern Asia ◽  
Hub Location ◽  
Hub Location Problem ◽  
Content Type ◽  
Western Asia

Purpose This paper aims to investigate the location of regional and international hub ports in liner shipping by proposing a hierarchical hub location problem. Design/methodology/approach This paper develops a mixed-integer linear programming model for the authors’ proposed problem. Numerical experiments based on a realistic Asia-Europe-Oceania liner shipping network are carried out to account for the effectiveness of this model. Findings The results show that one international hub port (i.e. Rotterdam) and one regional hub port (i.e. Zeebrugge) are opened in Europe. Two international hub ports (i.e. Sokhna and Salalah) are located in Western Asia, where no regional hub port is established. One international hub port (i.e. Colombo) and one regional hub port (i.e. Cochin) are opened in Southern Asia. One international hub port (i.e. Singapore) and one regional hub port (i.e. Jakarta) are opened in Southeastern Asia and Australia. Three international hub ports (i.e. Hong Kong, Shanghai and Yokohama) and two regional hub ports (i.e. Qingdao and Kwangyang) are opened in Eastern Asia. Originality/value This paper proposes a hierarchical hub location problem, in which the authors distinguish between regional and international hub ports in liner shipping. Moreover, scale economies in ship size are considered. Furthermore, the proposed problem introduces the main ports.

scholarly journals KGPMH: A hybrid approach for solving a novel facility location problem

2021 ◽  
Author(s):  
Maryam DehghanChenary ◽  
Arman Ferdowsi ◽  
Fariborz Jolai ◽  
Reza Tavakkoli-Moghaddam
Keyword(s):  
Mathematical Model ◽  
Location Problem ◽  
Hybrid Approach ◽  
Facility Location Problem ◽  
Evaluation Function ◽  
Genetic Approach ◽  
Hub Location ◽  
Hub Location Problem ◽  
Proposed Model ◽  
The Impact

<pre>The focus of this paper is to propose a bi-objective mathematical model for a new extension of a multi-period p-mobile hub location problem and then to devise an algorithm for solving it. The developed model considers the impact of the time spent traveling at the hubs' network, the time spent at hubs for processing the flows, and the delay caused by congestion at hubs with specific capacities. Following the unveiled model, a hybrid meta-heuristic algorithm will be devised that simultaneously takes advantage of a novel evaluation function, a clustering technique, and a genetic approach for solving the proposed model.</pre>

Multi-choice and stochastic programming for transportation problem involved in supply of foods and medicines to hospitals with consideration of logistic distribution

2020 ◽  
Vol 54 (4) ◽  
pp. 1119-1132
Author(s):  
Deshabrata Roy Mahapatra ◽  
Shibaji Panda ◽  
Shib Sankar Sana
Keyword(s):  
Stochastic Programming ◽  
Objective Function ◽  
Transportation Problem ◽  
Programming Model ◽  
Logistic Distribution ◽  
Programming Approach ◽  
Binary Variables ◽  
Cost Coefficient ◽  
Aspiration Levels ◽  
Stochastic Constraints

The objective of the proposed article is to minimize the transportation costs of foods and medicines from different source points to different hospitals by applying stochastic mathematical programming model to a transportation problem in a multi-choice environment containing the parameters in all constraints which follow the Logistic distribution and cost coefficients of objective function are also multiplicative terms of binary variables. Using the stochastic programming approach, the stochastic constraints are converted into an equivalent deterministic one. A transformation technique is introduced to manipulate cost coefficients of objective function involving multi-choice or goals for binary variables with auxiliary constraints. The auxiliary constraints depends upon the consecutive terms of multi-choice type cost coefficient of aspiration levels. A numerical example is presented to illustrate the whole idea.

scholarly journals A fuzzy programming approach for dynamic virtual hub location problem

2012 ◽  
Vol 36 (7) ◽  
pp. 3257-3270 ◽  
Author(s):  
Farzin Taghipourian ◽  
Iraj Mahdavi ◽  
Nezam Mahdavi-Amiri ◽  
Ahmad Makui
Keyword(s):  
Location Problem ◽  
Fuzzy Programming ◽  
Programming Approach ◽  
Hub Location ◽  
Hub Location Problem

scholarly journals A Bi-Level Programming Approach to the Location-Routing Problem with Cargo Splitting under Low-Carbon Policies

Mathematics ◽  
2021 ◽  
Vol 9 (18) ◽  
pp. 2325
Author(s):  
Cong Wang ◽  
Zhongxiu Peng ◽  
Xijun Xu
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Programming Model ◽  
Programming Approach ◽  
Low Carbon ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Routing ◽  
Level Model ◽  
The Impact

To identify the impact of low-carbon policies on the location-routing problem (LRP) with cargo splitting (LRPCS), this paper first constructs the bi-level programming model of LRPCS. On this basis, the bi-level programming models of LRPCS under four low-carbon policies are constructed, respectively. The upper-level model takes the engineering construction department as the decision-maker to decide on the distribution center’s location. The lower-level model takes the logistics and distribution department as the decision-maker to make decisions on the vehicle distribution route’s scheme. Secondly, the hybrid algorithm of Ant Colony Optimization and Tabu Search (ACO-TS) is designed, and an example is introduced to verify the model’s and algorithm’s effectiveness. Finally, multiple sets of experiments are designed to explore the impact of various low-carbon policies on the decision-making of the LRPCS. The experimental results show that the influence of the carbon tax policy is the greatest, the carbon trading and carbon offset policy have a certain impact on the decision-making of the LRPCS, and the influence of the emission cap policy is the least. Based on this, we provide the relevant low-carbon policies advice and management implications.

scholarly journals Megaregional Passenger Transportation Hub Location Problem Considering Congestion Effects

2021 ◽  
Vol 33 (4) ◽  
pp. 551-563
Author(s):  
Huang Yan ◽  
Xiaoning Zhang
Keyword(s):  
Location Problem ◽  
Travel Demand ◽  
Programming Model ◽  
Transportation Network ◽  
Network Capacity ◽  
Mixed Integer ◽  
Hub Location ◽  
Hub Location Problem ◽  
Passenger Transportation ◽  
Congestion Effects

The need to make effective plans for locating transportation hubs is of increasing importance in the megaregional area, as recent research suggests that the growing intercity travel demand affects the efficiency of a megaregional transportation system. This paper investigates a hierarchical facility location problem in a megaregional passenger transportation network. The aim of the study is to determine the locations of hub facilities at different hierarchical levels and distribute the demands to these facilities with minimum total cost, including investment, transportation, and congestion costs. The problem is formulated as a mixed-integer nonlinear programming model considering the service availability structure and hub congestion effects. A case study is designed to demonstrate the effectiveness of the proposed model in the Wuhan metropolitan area. The results show that the congestion effects can be addressed by reallocating the demand to balance the hub utilisation or constructing new hubs to increase the network capacity. The methods of appropriately locating hubs and distributing traffic flows are proposed to optimise the megaregional passenger transportation networks, which has important implications for decision makers.

A Stochastic Programming Approach for Locating and Dispatching Two Types of Ambulances

2021 ◽  
Vol 55 (2) ◽  
pp. 275-296
Author(s):  
Soovin Yoon ◽  
Laura A. Albert ◽  
Veronica M. White
Keyword(s):  
Stochastic Programming ◽  
Large Scale ◽  
Simulation Analysis ◽  
Programming Model ◽  
Prehospital Care ◽  
Programming Approach ◽  
Solution Technique ◽  
Solution Approach ◽  
Stochastic Solution ◽  
Problem Instances

Emergency Medical Service systems aim to respond to emergency calls in a timely manner and provide prehospital care to patients. This paper addresses the problem of locating multiple types of emergency vehicles to stations while taking into account that vehicles are dispatched to prioritized patients with different health needs. We propose a two-stage stochastic-programming model that determines how to locate two types of ambulances in the first stage and dispatch them to prioritized emergency patients in the second stage after call-arrival scenarios are disclosed. We demonstrate how the base model can be adapted to include nontransport vehicles. A model formulation generalizes the base model to consider probabilistic travel times and general utilities for dispatching ambulances to prioritized patients. We evaluate the benefit of the model using two case studies, a value of the stochastic solution approach, and a simulation analysis. The case study is extended to study how to locate vehicles in the model extension with nontransport vehicles. Stochastic-programming models are computationally challenging for large-scale problem instances, and, therefore, we propose a solution technique based on Benders cuts.

scholarly journals A Stochastic Programming Analysis of the Farm Level Implications of Soil Erosion Control

1985 ◽  
Vol 17 (2) ◽  
pp. 147-154 ◽  
Author(s):  
Eduardo Segarra ◽  
Randall A. Kramer ◽  
Daniel B. Taylor
Keyword(s):  
Stochastic Programming ◽  
Soil Loss ◽  
Programming Model ◽  
Farm Level ◽  
Farm Planning ◽  
Net Returns ◽  
Planning Models ◽  
Stochastic Programming Model ◽  
Programming Analysis ◽  
The Impact

AbstractThis paper analyzes the effects of uncertain soil loss in farm planning models. A disaggregated approach was used because of an interest in examining the impact of probabilistic soil loss constraints on farm level decisionmaking. A stochastic programming model was used to consider different levels of probability of soil loss. Traditional methods of analysis are shown to consistently overestimate net returns.

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