Risk-based Multiobjective Optimization Model for Bridge Maintenance Planning

2010 ◽  
Author(s):  
I-Tung Yang ◽  
Yen-Shun Hsu ◽  
Jane W. Z. Lu ◽  
Andrew Y. T. Leung ◽  
Vai Pan Iu ◽  
...  
Keyword(s):  
Multiobjective Optimization ◽  
Optimization Model ◽  
Maintenance Planning ◽  
Bridge Maintenance

scholarly journals Multiobjective Joint Optimization of Production Scheduling and Maintenance Planning in the Flexible Job-Shop Problem

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Jianfei Ye ◽  
Huimin Ma
Keyword(s):  
Decision Making ◽  
Optimization Model ◽  
Preventive Maintenance ◽  
Production Scheduling ◽  
Job Shop ◽  
Joint Optimization ◽  
Planning Problem ◽  
Flexible Job Shop ◽  
Maintenance Planning ◽  
Joint Decision

In order to solve the joint optimization of production scheduling and maintenance planning problem in the flexible job-shop, a multiobjective joint optimization model considering the maximum completion time and maintenance costs per unit time is established based on the concept of flexible job-shop and preventive maintenance. A weighted sum method is adopted to eliminate the index dimension. In addition, a double-coded genetic algorithm is designed according to the problem characteristics. The best result under the circumstances of joint decision-making is obtained through multiple simulation experiments, which proves the validity of the algorithm. We can prove the superiority of joint optimization model by comparing the result of joint decision-making project with the result of independent decision-making project under fixed preventive maintenance period. This study will enrich and expand the theoretical framework and analytical methods of this problem; it provides a scientific decision analysis method for enterprise to make production plan and maintenance plan.

Multiobjective Optimization Model for Prioritizing Transit Stops for ADA Improvements

2011 ◽  
Vol 137 (8) ◽  
pp. 580-588 ◽  
Author(s):  
Wanyang Wu ◽  
Albert Gan ◽  
Fabian Cevallos ◽  
Mohammed Hadi
Keyword(s):  
Multiobjective Optimization ◽  
Optimization Model

scholarly journals A Multiobjective Optimization Model for Continuous Allocation of Emergency Rescue Materials

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Yonghong Liu ◽  
Yucheng Li ◽  
De Huang
Keyword(s):  
Multiobjective Optimization ◽  
Optimization Model ◽  
Supply And Demand ◽  
Economic Losses ◽  
Allocation Scheme ◽  
Nsga Ii ◽  
Pareto Solution ◽  
Emergency Relief ◽  
Rescue Work ◽  
Emergency Rescue

Emergency rescue operations play a vital role in alleviating human suffering, reducing casualties, and cutting down economic losses. One key aspect in the management of these operations is the rational allocation of emergency relief materials, where the allocation is continuous, dynamic, and concurrent. This allocation should be made not only to minimize the emergency rescue losses, but also to reduce the cost of emergency rescue work. A reasonable and effective allocation scheme for emergency relief materials can be established to adapt to the continuity, dynamics, and concurrency of material distribution. In this work, we propose a multiobjective optimization model of emergency material allocation with continuous time-varying supply and demand constraints, where the objective is to minimize the losses and the economic cost incurred by the emergency rescue operations. The constrained optimization problem is handled through sequential unconstrained minimization techniques, and the multiobjective optimization is carried out by the fast nondominated sorting genetic algorithm (NSGA-II) with an elite strategy to obtain a Pareto solution set with fairness and balance of loss and cost. The loss and cost associated with the Pareto frontier are employed to find an appropriate noninferior solution and its corresponding material allocation scheme. We verify through several simulations the model feasibility and the effectiveness of the proposed method, which can provide decision support for continuous material allocation in emergency rescue operations.

A multiobjective optimization model for sustainable reverse logistics in Indian E-commerce market

2020 ◽  
Vol 249 ◽  
pp. 119348 ◽  
Author(s):  
Pankaj Dutta ◽  
Anurag Mishra ◽  
Sachin Khandelwal ◽  
Ibrahim Katthawala
Keyword(s):  
Multiobjective Optimization ◽  
Reverse Logistics ◽  
Optimization Model

Multi objective optimization for humanitarian logistics operations through the use of mobile technologies

2016 ◽  
Vol 6 (3) ◽  
pp. 399-418 ◽  
Author(s):  
Marco Antonio Serrato-Garcia ◽  
Jaime Mora-Vargas ◽  
Roman Tomas Murillo
Keyword(s):  
Decision Making ◽  
Information System ◽  
Developing Countries ◽  
Multiobjective Optimization ◽  
Mobile Technology ◽  
Optimization Model ◽  
Humanitarian Logistics ◽  
Social Costs ◽  
Content Type ◽  
Deprivation Costs

Purpose The purpose of this paper is to present the development and implementation of a multiobjective optimization model and information system based on mobile technology, to support decision making in humanitarian logistics operations. Design/methodology/approach The trade-off between economic and social (deprivation) costs faced by governmental and nongovernmental organizations (NGOs) involved in humanitarian logistics operations is modeled through a Pareto frontier analysis, which is obtained from a multiobjective optimization model. Such analysis is supported on an information system based on mobile technology. Findings Results show useful managerial insights for decision-makers by considering both economic and social costs associated to humanitarian logistics operations. Such insights include the importance of timely and accurate information shared through mobile technology. Research limitations/implications This research presents a multiobjective approach that considers social costs, which are modeled through deprivation functions. The authors suggest that a future nonlinear approach be also considered, since there will be instances where the deprivation cost is a nonlinear function throughout time. Also, the model and information system developed may not be suitable for other humanitarian aid instances, considering the specific characteristics of the events considered on this research. Practical implications The inclusion of several types of goods, vehicles, collecting points off the ground, distributions points on the ground, available roads after a disaster took place, as well as volume and weight constraints faced under these scenarios, are considered. Social implications Deprivation costs faced by affected population after a disaster took place are considered, which supports decision making in governmental and NGOs involved in humanitarian logistics operations toward welfare of such affected population in developing countries. Originality/value A numerical illustration in the Latin American context is presented, the model and information system developed can be used in other developing countries or regions that face similar challenges toward humanitarian logistics operations.

scholarly journals Research on Taxi Pricing Model and Optimization for Carpooling Detour Problem

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Wei Zhang ◽  
Ruichun He ◽  
Yong Chen ◽  
Mingxia Gao ◽  
Changxi Ma
Keyword(s):  
Genetic Algorithm ◽  
Multiobjective Optimization ◽  
Optimization Model ◽  
Travel Distance ◽  
Important Influence ◽  
Pricing Model ◽  
Fair Pricing ◽  
Maximum Value ◽  
Pricing Scheme

This paper builds a multiobjective optimization model for solving the taxi carpooling with detour problem and designs a genetic algorithm to determine a fair pricing scheme for riders and drivers. The researches show that it is feasible to share a taxi with detour. It is the key to determine appropriate carpooling payment ratio and detour carpooling payment ratio. The ratio of detour distance to travel distance has an important influence on detour carpooling. It should be limited to less than certain values. Payment ratios and the maximum value of the ratio of detour distance to travel distance are determined by the method proposed in this paper. The method can ensure benefits of passengers and drivers, which makes detour carpooling a reality. These conclusions and the method have a certain guiding significance for formulating taxi policy.

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