scholarly journals Multi-phase and Integrated Multi-objective Cyclic Operating Room Scheduling Based on an Improved NSGA-ⅡApproach

Symmetry ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 599 ◽  
Author(s):  
Qian Lu ◽  
Xiaomin Zhu ◽  
Dong Wei ◽  
Kaiyuan Bai ◽  
Jinsheng Gao ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Operating Room ◽  
Programming Model ◽  
Second Phase ◽  
Nsga Ii ◽  
Surgical Specialty ◽  
Allocation Model ◽  
Multi Objective ◽  
Proposed Model ◽  
Multi Phase

The operating room (OR) is an important department in a hospital, and the scheduling of surgeries in ORs is a challenging combinatorial optimization problem. In this paper, we address the problem of multiple resource allocation of ORs and propose a surgery scheduling scheme for OR units. To solve this problem, a multi-phase and integrated multi-objective linear programming model is proposed. The first phase of the proposed model is a resource allocation model, which mainly focuses on the allocation of ORs for each surgical specialty (SS). Based on the results of the first phase, the second phase is the cyclic Master Surgical Schedule model, which aims to schedule the surgeries in each SS. The proposed models are solved by the Non-dominated Sorting Genetic Algorithm II (NSGA-II), which was improved. Finally, two numerical experiments based on practical data are provided to verify the effectiveness of the proposed models as well as to evaluate the performance of the improved NSGA-II. Our final results illustrate that our proposed model can provide hospital managers with a series of “optimal” solutions to effectively allocate relevant resources and ORs for surgeries, and they show that the improved NSGA-II has high computational efficiency and is more suitable in solving larger-scale problems.

scholarly journals Multi-objective optimal allocation of water resources based on ‘three red lines’ in Qinzhou, China

Water Policy ◽  
2020 ◽  
Vol 22 (4) ◽  
pp. 541-560
Author(s):  
Haopeng Guan ◽  
Lihua Chen ◽  
Shuping Huang ◽  
Cheng Yan ◽  
Yan Wang
Keyword(s):  
Resource Allocation ◽  
Water Resources ◽  
Water Resource ◽  
Optimal Allocation ◽  
Supply And Demand ◽  
Domestic Water ◽  
Nsga Ii ◽  
Allocation Model ◽  
Water Resource Allocation ◽  
Multi Objective

Abstract Water shortages and pollution emerge because of anthropogenic demands. Since 2011, ‘China's Most Stringent Water Resources Management’ (CMSWRM) has been comprehensively enacted in the country. This paper presents the characteristics of the ‘three red lines’ (TRL) and a multi-objective optimal allocation model based on the TRL constraint, considering the benefits for society, the economy, and the environment. This model had been applied to the reasonable allocation of water supply and demand in Qinzhou for the planning years of 2020 and 2030. Two water resource allocation scenarios for these years were configured by setting different chemical oxygen demand (COD) concentrations for wastewater discharge in the municipal, secondary, tertiary, and agricultural sectors. The gamultiobj function based on the NSGA-II algorithm was used to solve the model in MATLAB. The results indicate that if COD concentrations in each sector are not reduced, then restrictions on domestic water sources will be necessary, both in 2020 and 2030. The two water resource allocation scenarios in 2020 and 2030 can provide a reference for decision-makers in Qinzhou to implement CMSWRM.

scholarly journals Healthcare Facility Location-Allocation Optimization for China’s Developing Cities Utilizing a Multi-Objective Decision Support Approach

2018 ◽  
Vol 10 (12) ◽  
pp. 4580 ◽  
Author(s):  
Li Wang ◽  
Huan Shi ◽  
Lu Gan
Keyword(s):  
Heuristic Algorithms ◽  
Programming Model ◽  
Rapid Development ◽  
Supply And Demand ◽  
Healthcare Facility ◽  
Allocation Model ◽  
Location Allocation ◽  
Multi Objective ◽  
Conflicting Objectives ◽  
Allocation Problems

With rapid development of the healthcare network, the location-allocation problems of public facilities under increased integration and aggregation needs have been widely researched in China’s developing cites. Since strategic formulation involves multiple conflicting objectives and stakeholders, this paper presents a practicable hierarchical location-allocation model from the perspective of supply and demand to characterize the trade-off between social, economical and environmental factors. Due to the difficulties of rationally describing and the efficient calculation of location-allocation problems as a typical Non-deterministic Polynomial-Hard (NP-hard) problem with uncertainty, there are three crucial challenges for this study: (1) combining continuous location model with discrete potential positions; (2) introducing reasonable multiple conflicting objectives; (3) adapting and modifying appropriate meta-heuristic algorithms. First, we set up a hierarchical programming model, which incorporates four objective functions based on the actual backgrounds. Second, a bi-level multi-objective particle swarm optimization (BLMOPSO) algorithm is designed to deal with the binary location decision and capacity adjustment simultaneously. Finally, a realistic case study contains sixteen patient points with maximum of six open treatment units is tested to validate the availability and applicability of the whole approach. The results demonstrate that the proposed model is suitable to be applied as an extensive planning tool for decision makers (DMs) to generate policies and strategies in healthcare and design other facility projects.

scholarly journals A Multiobjective Allocation Model for Emergency Resources That Balance Efficiency and Fairness

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Yanyan Wang ◽  
Baiqing Sun
Keyword(s):  
Resource Allocation ◽  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Allocation Model ◽  
Swarm Optimization ◽  
Emergency Relief ◽  
Resource Allocation Model ◽  
Proposed Model ◽  
Emergency Resource

Efficiency and fairness are two important goals of disaster rescue. However, the existing models usually unilaterally consider the efficiency or fairness of resource allocation. Based on this, a multiobjective emergency resource allocation model that can balance efficiency and fairness is proposed. The object of the proposed model is to minimize the total allocating costs of resources and the total losses caused by insufficient resources. Then the particle swarm optimization is applied to solve the model. Finally, a computational example is conducted based on the emergency relief resource allocation after Ya’an earthquake in China to verify the applicability of the proposed model.

A Bi-objective Multi-Product Multi-Constraint EPQ Model in a Stochastic Environment and Partial Shortage

2020 ◽  
Vol 19 (03) ◽  
pp. 567-587
Author(s):  
Seyedeh Sanaz Mirkhorsandi ◽  
Seyed Hamid Reza Pasandideh
Keyword(s):  
Goal Attainment ◽  
Programming Model ◽  
Multi Objective ◽  
Holding Costs ◽  
Inventory Costs ◽  
Economic Production ◽  
Proposed Model ◽  
Demand Rate ◽  
Nonlinear Programming Model ◽  
Epq Model

One of the classical models for inventory control is economic production quantity (EPQ), which is widely used in industry. In this paper, an EPQ model with partial shortage is developed by considering the real world conditions, and costs related to the backorder demand are taken as fixed and time-dependent. In the proposed model, determination of the inventory cycle length, the length of positive inventory cycle and backordered demand rate are considered in shortage period. The aim of the presented research is to minimize the total inventory costs and the space required for storage products so that the stochastic and classic constraints including holding costs, lost sales, backorder, budget, total number of productions and average shortage times should be satisfied while optimizing the multi-objective problem. Presented model is a bi-objective nonlinear programming model. Then, to solve the proposed model, three multi-objective decision-making methods including Lp-metric, goal programming and goal attainment are used. Besides, numerical examples are executed in small, medium and large scales by use of GAMS software, and the performance of the methods is compared in terms of objective functions and required CPU time. Finally, sensitivity analysis is done to determine the effect of change in the main parameters of the model on the objective function value.

Multi-Objective Optimization of Human Resource Allocation in Production Cells with Different Training Modes

2012 ◽  
Vol 601 ◽  
pp. 521-525
Author(s):  
Cai Juan Li ◽  
Xiao Yun Wu ◽  
Xiao Dong Zhang
Keyword(s):  
Resource Allocation ◽  
Staff Training ◽  
Programming Model ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
The People ◽  
Training Mode ◽  
The Difference ◽  
Production Cell

Aiming at the difference of the people as a particularity resource。In this paper ,the personnel training mode is divided into junior and senior, and a multi-objective integer programming model is established at the lowest cost of staff training, the highest man-machine adaptability degree and minimum personnel workload. Calculating example of a real production cell is presented. The results show that the model is correct and the necessity for classification of training modes.The model can help the management to adopt reasonable training mode and achieve desirable objectives.

scholarly journals A Location-Procurement-Distribution Model Combined with Data Envelopment Analysis Model under a Multi-period Environment and Gradual Budget Injection for Humanitarian Relief Supply Chains

2021 ◽  
Author(s):  
Leyla Fazli
Keyword(s):  
Data Envelopment Analysis ◽  
Programming Model ◽  
Mixed Integer ◽  
Distribution Model ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Humanitarian Relief ◽  
Analysis Model ◽  
Multi Objective ◽  
Proposed Model

Abstract Humanmade or natural catastrophes such as droughts, floods, earthquakes, storms, coups, economic and political crises, wars, and so forth impact various areas of the world annually. Furthermore, the lack of adequate preparations and proper coping against them causes nations to suffer heavy losses and casualties, which are sometimes irrecoverable. Consequently, as an essential activity in crisis management, humanitarian relief logistics has been of particular importance and has taken a good deal of notice at the international level during recent years. Aid facilities location and the storage of necessary commodities before a disaster and the proper distribution of relief commodities among demand points following a disaster are critical logistical strategies to improve performance and reduce latency when responding to a given disaster. In this regard, this study presents a stochastic multi-objective mixed-integer non-linear programming model in a two-level network that includes warehouses and affected areas. The model aims at minimizing total social costs, which include the expense of founding warehouses, the expense of procuring commodities, and deprivation cost, as well as maximizing fulfilled demands and warehouses utility. In this study, several pre-disaster periods, a limited budget for establishing warehouses and procuring relief commodities with their gradual injection into the system, the time value of money, various criteria for evaluating warehouses, the risk of disruption in warehouses and transportation networks, and heterogeneous warehouses are considered. The maximization of warehouses utility is done according to a data envelopment analysis model. Moreover, a multi-objective fuzzy programming model called the weighted max-min model is applied to solve the proposed model. Ultimately, the outcomes of the evaluation and validation of the proposed model show its appropriate and efficient performance.

scholarly journals A multi-objective selective maintenance optimization method for series-parallel systems using NSGA-III and NSGA-II evolutionary algorithms

2021 ◽  
Vol 16 (3) ◽  
pp. 372-384
Author(s):  
E.B. Xu ◽  
M.S. Yang ◽  
Y. Li ◽  
X.Q. Gao ◽  
Z.Y. Wang ◽  
...  
Keyword(s):  
Rest Period ◽  
Optimization Method ◽  
Parallel System ◽  
Maintenance Cost ◽  
Nsga Ii ◽  
Allocation Model ◽  
Multi Objective ◽  
Objective Model ◽  
Selective Maintenance ◽  
Personnel Allocation

Aiming at the problem that the downtime is simply assumed to be constant and the limited resources are not considered in the current selective maintenance of the series-parallel system, a three-objective selective maintenance model for the series-parallel system is established to minimize the maintenance cost, maximize the probability of completing the next task and minimize the downtime. The maintenance decision-making model and personnel allocation model are combined to make decisions on the optimal length of each equipment’s rest period, the equipment to be maintained during the rest period and the maintenance level. For the multi-objective model established, the NSGA-III algorithm is designed to solve the model. Comparing with the NSGA-II algorithm that only considers the first two objectives, it is verified that the designed multi-objective model can effectively reduce the downtime of the system.

scholarly journals Using NSGAII to Solve Bi-objective Bed Allocation Problems

2015 ◽  
Vol 1 (3) ◽  
pp. 397
Author(s):  
Jalal A. Sultan ◽  
Ban A. Mitras ◽  
Raghad M. Jasim
Keyword(s):  
Queuing Theory ◽  
Optimization Problems ◽  
Admission Rate ◽  
Nsga Ii ◽  
Multi Objective ◽  
Decision Aiding ◽  
Proposed Model ◽  
Objective Model ◽  
Bed Allocation ◽  
Suitable Framework

The Bed Allocation Problem (BAP) is NP-complete and always high dimensional. In this paper, a bi-objective decision aiding model based on queuing theory is introduced for allocation of beds in a hospital. The problem is modeled as an M/PH/n queue. The objectives include maximizing the patient admission rate human resources, in particular, maximization of the nursing work hours. The proposed model is solved by using Non-dominated Sorting Genetic Algorithm-II (NSGA-II), which is a very effective algorithm for solving multi-objective optimization problems and finding optimal Pareto front. The paper describes an application of the model, dealing with a public hospital in Iraq. The results related that multi-objective model was presented suitable framework for bed allocation and optimum use.

Resource Allocation Model Toward Seismic Water Pipeline Risk Mitigation Measures

2019 ◽  
Author(s):  
Elnaz Peyghaleh ◽  
Tarek Alkhrdaji
Keyword(s):  
Resource Allocation ◽  
Risk Analysis ◽  
Seismic Hazard ◽  
Seismic Risk ◽  
Distribution Systems ◽  
Risk Mitigation ◽  
Mitigation Measures ◽  
Seismic Risk Analysis ◽  
Allocation Model ◽  
Proposed Model

Abstract History of earthquake’s damages have illustrated the high vulnerability and risks associated with failure of water transfer and distribution systems. Adequate mitigation plans to reduce such seismic risks are required for sustainable development. The first step in developing a mitigation plan is prioritizing the limited available budget to address the most critical mitigation measures. This paper presents an optimization model that can be utilized for financial resource allocation towards earthquake risk mitigation measures for water pipelines. It presents a framework that can be used by decision-makers (authorities, stockholders, owners and contractors) to structure budget allocation strategy for seismic risk mitigation measures such as repair, retrofit, and/or replacement of steel and concrete pipelines. A stochastic model is presented to establish optimal mitigation measures based on minimizing repair and retrofit costs, post-earthquake replacement costs, and especially earthquake-induced large losses. To consider the earthquake induced loss on pipelines, the indirect loss due to water shortage and business interruption in the industries which needs water is also considered. The model is applied to a pilot area to demonstrate the practical application aspects of the proposed model. Pipeline exposure database, built environment occupancy type, pipeline vulnerability functions, and regional seismic hazard characteristics are used to calculate a probabilistic seismic risk for the pilot area. The Global Earthquake Model’s (GEM) OpenQuake software is used to run various seismic risk analysis. Event-based seismic hazard and risk analyses are used to develop the hazard curves and maps in terms of peak ground velocity (PGV) for the study area. The results of this study show the variation of seismic losses and mitigation costs for pipelines located within the study area based on their location and the types of repair. Performing seismic risk analysis analyses using the proposed model provides a valuable tool for determining the risk associated with a network of pipelines in a region, and the costs of repair based on acceptable risk level. It can be used for decision making and to establish type and budgets for most critical repairs for a specific region.

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