A maximal covering facility location model for emergency services within an M (t)/M/m/m queuing system

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Iman Bahrami ◽  
Roya M. Ahari ◽  
Milad Asadpour
Keyword(s):  
Facility Location ◽  
Emergency Services ◽  
Queuing System ◽  
Location Model ◽  
Computational Time ◽  
Nsga Ii ◽  
Content Type ◽  
Maximal Covering ◽  
Proposed Model

Purpose In emergency services, maximizing population coverage with the lowest cost at the peak of the demand is important. In addition, due to the nature of services in emergency centers, including hospitals, the number of servers and beds is actually considered as the capacity of the system. Hence, the purpose of this paper is to propose a multi-objective maximal covering facility location model for emergency service centers within an M (t)/M/m/m queuing system considering different levels of service and periodic demand rate. Design/methodology/approach The process of serving patients is modeled according to queuing theory and mathematical programming. To cope with multi-objectiveness of the proposed model, an augmented ε-constraint method has been used within GAMS software. Since the computational time ascends exponentially as the problem size increases, the GAMS software is not able to solve large-scale problems. Thus, a NSGA-II algorithm has been proposed to solve this category of problems and results have been compared with GAMS through random generated sample problems. In addition, the applicability of the proposed model in real situations has been examined within a case study in Iran. Findings Results obtained from the random generated sample problems illustrated while both the GAMS software and NSGA-II almost share the same quality of solution, the CPU execution time of the proposed NSGA-II algorithm is lower than GAMS significantly. Furthermore, the results of solving the model for case study approve that the model is able to determine the location of the required facilities and allocate demand areas to them appropriately. Originality/value In the most of previous works on emergency services, maximal coverage with the minimum cost were the main objectives. Hereby, it seems that minimizing the number of waiting patients for receiving services have been neglected. To the best of the authors’ knowledge, it is the first time that a maximal covering problem is formulated within an M (t)/M/m/m queuing system. This novel formulation will lead to more satisfaction for injured people by minimizing the average number of injured people who are waiting in the queue for receiving services.

scholarly journals Impact of Prioritization on the Outpatient Queuing System in the Emergency Department with Limited Medical Resources

Symmetry ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 796 ◽  
Author(s):  
Ao Zhang ◽  
Xiaomin Zhu ◽  
Qian Lu ◽  
Runtong Zhang
Keyword(s):  
Emergency Department ◽  
Emergency Services ◽  
Service System ◽  
Queuing System ◽  
Hospital Service ◽  
Key Factors ◽  
Queuing Model ◽  
Medical Resources ◽  
Proposed Model

The emergency department has an irreplaceable role in the hospital service system because of the characteristics of its emergency services. In this paper, a new patient queuing model with priority weight is proposed to optimize the management of emergency department services. Compared with classical queuing rules, the proposed model takes into consideration the key factors of service and the first-come-first-served queuing rule in emergency services. According to some related queuing indicators, the optimization of emergency services is discussed. Finally, a case study and some compared analysis are conducted to illustrate the practicability of the proposed model.

Modeling of the time-dependent multi-skilled RCPSP considering learning effect

2019 ◽  
Vol 14 (2) ◽  
pp. 521-558 ◽  
Author(s):  
Amir Hossein Hosseinian ◽  
Vahid Baradaran ◽  
Mahdi Bashiri
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Learning Effect ◽  
The Other ◽  
Time Dependent ◽  
Computational Time ◽  
Nsga Ii ◽  
Content Type ◽  
Proposed Model ◽  
Objective Function Values

Purpose The purpose of this paper is to propose a new mixed-integer formulation for the time-dependent multi-skilled resource-constrained project scheduling problem (MSRCPSP/t) considering learning effect. The proposed model extends the basic form of the MSRCPSP by three concepts: workforces have different efficiencies, it is possible for workforces to improve their efficiencies by learning from more efficient workers and the availability of workforces and resource requests of activities are time-dependent. To spread dexterity from more efficient workforces to others, this study has integrated the concept of diffusion maximization in social networks into the proposed model. In this respect, the diffusion of dexterity is formulated based on the linear threshold model for a network of workforces who share common skills. The proposed model is bi-objective, aiming to minimize make-span and total costs of project, simultaneously. Design/methodology/approach The MSRCPSP is an non-deterministic polynomial-time hard (NP-hard) problem in the strong sense. Therefore, an improved version of the non-dominated sorting genetic algorithm II (IM-NSGA-II) is developed to optimize the make-span and total costs of project, concurrently. For the proposed algorithm, this paper has designed new genetic operators that help to spread dexterity among workforces. To validate the solutions obtained by the IM-NSGA-II, four other evolutionary algorithms – the classical NSGA-II, non-dominated ranked genetic algorithm, Pareto envelope-based selection algorithm II and strength Pareto evolutionary algorithm II – are used. All algorithms are calibrated via the Taguchi method. Findings Comprehensive numerical tests are conducted to evaluate the performance of the IM-NSGA-II in comparison with the other four methods in terms of convergence, diversity and computational time. The computational results reveal that the IM-NSGA-II outperforms the other methods in terms of most of the metrics. Besides, a sensitivity analysis is implemented to investigate the impact of learning on objective function values. The outputs show the significant impact of learning on objective function values. Practical implications The proposed model and algorithm can be used for scheduling activities of small- and large-size real-world projects. Originality/value Based on the previous studies reviewed in this paper, one of the research gaps is the MSRCPSP with time-dependent resource capacities and requests. Therefore, this paper proposes a multi-objective model for the MSRCPSP with time-dependent resource profiles. Besides, the evaluation of learning effect on efficiency of workforces has not been studied sufficiently in the literature. In this study, the effect of learning on efficiency of workforces has been considered. In the scarce number of proposed models with learning effect, the researchers have assumed that the efficiency of workforces increases as they spend more time on performing a skill. To the best of the authors’ knowledge, the effect of learning from more efficient co-workers has not been studied in the literature of the RCPSP. Therefore, in this research, the effect of learning from more efficient co-workers has been investigated. In addition, a modified version of the NSGA-II algorithm is developed to solve the model.

A practical supply-demand hub in industrial clusters: a new perspective

2019 ◽  
Vol 42 (1) ◽  
pp. 68-101 ◽  
Author(s):  
Vahid Kayvanfar ◽  
S.M. Moattar Husseini ◽  
Zhang NengSheng ◽  
Behrooz Karimi ◽  
Mohsen S. Sajadieh
Keyword(s):  
Sensitivity Analysis ◽  
Supply Chain ◽  
Raw Materials ◽  
Industrial Clusters ◽  
Computational Time ◽  
Heuristic Procedure ◽  
Content Type ◽  
Proposed Model ◽  
Practical Implications

PurposeThis paper aims to optimize the interactions of businesses located within industrial clusters (ICs) by using a supply-demand hub in ICs (SDHIC) as a conjoint provider of logistics and depository facilities for small- and medium-sized enterprises (SMEs) as producers, where all of these interactions are under supervision of a third-party logistics provider (3PL).Design/methodology/approachTo evaluate the values of SDHIC, three mathematical models are proposed, optimally solved via GAMS and then compared. Also, a “linear relaxation-based heuristic” procedure is proposed to yield a feasible initial solution within a significant shorter computational time. To illustrate the values of SDHIC, comprehensive calculations over a case study and generated sets of instances are conducted, including several sensitivity analysis.FindingsThe experimental results demonstrate the efficiency of SDHIC for SMEs via combining batches and integrating the holding space of inventories, while the outcomes of the case study are aligned with those obtained from random sample examples, which confirms the trueness of used parameters and reveals the applicability of using SDHIC in real world. Finally, several interesting managerial implications for practitioners are extracted and presented.Practical implicationsSome of the managerial and practical implications are optimizing interactions of businesses involved in a supply chain of an IC containing some customers, suppliers and manufacturers and rectifying the present noteworthy gaps pertaining to the previously published research via using real assumptions and merging upstream and downstream of the supply chain through centralizing on storage of raw materials (supply echelon) and finished products (demand echelon) at the same place simultaneously to challenge a classic concept in which supply and demand echelons were being separately planned regarding their inventory management and logistics activities and showing the positive consequences of such challenge, showing the performance improvement of the proposed model compared to the classic model, by increasing the storing cost of raw materials and finished products, considering some disadvantages of using SDHIC and showing the usefulness of SDHIC in total, presenting some applied findings according to the obtained results of sensitivity analysis.Originality/valueThe key contributions of this paper to the literature are suggesting a new applied mathematical methodology to the supply chain (SC) of ICs by means of a conjoint provider of warehousing activities called SDHIC, comparing the new proposed model with the two classic ones and showing the proposed model’s dominancy, showing the helpful outcomes of collaborating 3PL with the SMEs in a cluster, proposing a “linear relaxation-based heuristic” procedure to yield a feasible initial solution within a significant shorter computational time and minimizing total supply chain costs of such IC by optimum application of facilities, lands and labor.

A bi-level mathematical model for logistic management considering the evolutionary game with environmental feedbacks

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Peiman Ghasemi ◽  
Fariba Goodarzian ◽  
Angappa Gunasekaran ◽  
Ajith Abraham
Keyword(s):  
Mathematical Model ◽  
Lagrangian Relaxation ◽  
Evolutionary Games ◽  
Relaxation Method ◽  
Objective Functions ◽  
Content Type ◽  
Medical Centers ◽  
Location Routing ◽  
Proposed Model

PurposeThis paper proposed a bi-level mathematical model for location, routing and allocation of medical centers to distribution depots during the COVID-19 pandemic outbreak. The developed model has two players including interdictor (COVID-19) and fortifier (government). Accordingly, the aim of the first player (COVID-19) is to maximize system costs and causing further damage to the system. The goal of the second player (government) is to minimize the costs of location, routing and allocation due to budget limitations.Design/methodology/approachThe approach of evolutionary games with environmental feedbacks was used to develop the proposed model. Moreover, the game continues until the desired demand is satisfied. The Lagrangian relaxation method was applied to solve the proposed model.FindingsEmpirical results illustrate that with increasing demand, the values of the objective functions of the interdictor and fortifier models have increased. Also, with the raising fixed cost of the established depot, the values of the objective functions of the interdictor and fortifier models have raised. In this regard, the number of established depots in the second scenario (COVID-19 wave) is more than the first scenario (normal COVID-19 conditions).Research limitations/implicationsThe results of the current research can be useful for hospitals, governments, Disaster Relief Organization, Red Crescent, the Ministry of Health, etc. One of the limitations of the research is the lack of access to accurate information about transportation costs. Moreover, in this study, only the information of drivers and experts about transportation costs has been considered. In order to implement the presented solution approach for the real case study, high RAM and CPU hardware facilities and software facilities are required, which are the limitations of the proposed paper.Originality/valueThe main contributions of the current research are considering evolutionary games with environmental feedbacks during the COVID-19 pandemic outbreak and location, routing and allocation of the medical centers to the distribution depots during the COVID-19 outbreak. A real case study is illustrated, where the Lagrangian relaxation method is employed to solve the problem.

An M/M/C/K queueing system in an inventory routing problem considering congestion and response time for post-disaster humanitarian relief: a case study

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mahdieh Masoumi ◽  
Amir Aghsami ◽  
Mohammad Alipour-Vaezi ◽  
Fariborz Jolai ◽  
Behdad Esmailifar
Keyword(s):  
Sensitivity Analyses ◽  
Inventory Routing ◽  
Humanitarian Relief ◽  
Exact Methods ◽  
Routing Problem ◽  
Content Type ◽  
Inventory Routing Problem ◽  
The People ◽  
Proposed Model

PurposeDue to the randomness and unpredictability of many disasters, it is essential to be prepared to face difficult conditions after a disaster to reduce human casualties and meet the needs of the people. After the disaster, one of the most essential measures is to deliver relief supplies to those affected by the disaster. Therefore, this paper aims to assign demand points to the warehouses as well as routing their related relief vehicles after a disaster considering convergence in the border warehouses.Design/methodology/approachThis research proposes a multi-objective, multi-commodity and multi-period queueing-inventory-routing problem in which a queuing system has been applied to reduce the congestion in the borders of the affected zones. To show the validity of the proposed model, a small-size problem has been solved using exact methods. Moreover, to deal with the complexity of the problem, a metaheuristic algorithm has been utilized to solve the large dimensions of the problem. Finally, various sensitivity analyses have been performed to determine the effects of different parameters on the optimal response.FindingsAccording to the results, the proposed model can optimize the objective functions simultaneously, in which decision-makers can determine their priority according to the condition by using the sensitivity analysis results.Originality/valueThe focus of the research is on delivering relief items to the affected people on time and at the lowest cost, in addition to preventing long queues at the entrances to the affected areas.

A multi-attribute approach to select the best method for repairing river bridge columns

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mitra Salmaninezhad ◽  
S. Mahmood Jazayeri Moghaddas
Keyword(s):  
Evaluation Criteria ◽  
Bridge Columns ◽  
Pier Scour ◽  
Content Type ◽  
Accuracy And Precision ◽  
Proposed Model ◽  
Research Findings ◽  
Multi Attribute Decision Making ◽  
Weighing Method

PurposePier scour is one of the main causes of damage to the columns of the river bridges. It is essential to select the best method among various repair methods based on different evaluation indices. However, there is no procedure for ranking these repair methods based on their attributes. The present study seeks to set an approach for this ranking.Design/methodology/approachIn this paper, a multi-attribute decision-making (MADM) model is presented for ranking the repair techniques, in which alternatives are examined using the most important evaluation criteria. In addition, a combination of entropy and eigenvector methods has been proposed for weighting these attributes. A case study is then used to demonstrate the applicability and the validity of the method.FindingsThe execution of the model using two multi-criteria methods yielded similar results, which confirms its accuracy and precision. Moreover, the research findings showed the consistency of the objective and subjective weighting methods and the conformity of the weights obtained for the attributes from the combination of these methods to the nature of the problem.Originality/valueThe selection of the proper method for repairing the bridge columns plays an essential role in success of the bridge restoration. The proposed model introduces an approach for ranking repair methods and selecting the best one that has not been presented so far. Also, the weighing method for attributes is an innovative method for ranking restoration methods that has been proven in a case study.

scholarly journals Waiting time in public hospitals: case study of total joint replacement in Hong Kong

2018 ◽  
Vol 21 (2) ◽  
pp. 120-133 ◽  
Author(s):  
Yee-man Tsui ◽  
Ben Y.F. Fong
Keyword(s):  
Hong Kong ◽  
Waiting Time ◽  
Joint Replacement ◽  
Process Management ◽  
Emergency Services ◽  
Total Joint Replacement ◽  
Care Quality ◽  
Public Hospitals ◽  
Content Type

Purpose The purpose of this paper is to review the causes of long waiting time in Hong Kong public hospitals and to suggest solutions in the service, organisational, systems, financial and policy perspectives. Design/methodology/approach The paper is a review of waiting time of public hospital services. Total joint replacement, which is one of the elective surgeries in public hospitals, is presented as a case study. Findings The average waiting time of semi-urgent and non-urgent patients in the accident and emergency departments of public hospitals is two hours, and that of specialist outpatient (SOP) clinics is from 1 to 144 weeks. For total joint replacement, it is from 36 to 110 months. Measures like Government subsidisation programme for the replacement surgery and employing adequate physiotherapists, Chinese medicine practitioners, clinical psychologists and nurses to reduce the waiting time are suggested. Issues concerning the healthcare system of Hong Kong, such as structural reform, service delivery model, primary care, quality and process management, and policy reviews, are also discussed. Originality/value The ‬over-reliance of public services has resulted in long waiting time in public hospitals in Hong Kong, particularly in the emergency services and SOP clinics. However, the consequences of long waiting period for surgical operations, though much less discussed by the media and public, can be potentially detrimental to the patients and families, and may result in more burdens to the already stretched public hospitals‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬.

A novel product recommendation model consolidating price, trust and online reviews

Kybernetes ◽  
2019 ◽  
Vol 48 (6) ◽  
pp. 1355-1372 ◽  
Author(s):  
Ying Huang ◽  
Nu-nu Wang ◽  
Hongyu Zhang ◽  
Jianqiang Wang
Keyword(s):  
Search Engines ◽  
Distance Measure ◽  
Fuzzy Theory ◽  
Online Reviews ◽  
Purchasing Decisions ◽  
Neutrosophic Sets ◽  
Content Type ◽  
Product Recommendation ◽  
Proposed Model

Purpose The purpose of this paper is to propose a model for product recommendation to improve the accuracy of recommendation based on the current search engines used in e-commerce platforms like Tmall.com. Design/methodology/approach First, the proposed model comprehensively considers price, trust and online reviews, which all represent critical factors in consumers’ purchasing decisions. Second, the model introduces the quantization methods for these criteria incorporating fuzzy theory. Third, the model uses a distance measure between two single valued neutrosophic sets based on the prioritized average operator to consolidate the influences of positive, neutral and negative comments. Finally, the model uses multi-criteria decision-making methods to integrate the influences of price, trust and online reviews on purchasing decisions to generate recommendations. Findings To demonstrate the feasibility and efficiency of the proposed model, a case study is conducted based on Tmall.com. The results of case study indicate that the recommendations of our model perform better than those of current search engines of Tmall.com. The proposed model can significantly improve the accuracy of product recommendations based on search engines. Originality/value The product recommendation method can meet the critical challenge from the search engines on e-commerce platforms. In addition, the proposed method could be used in practice to develop a new application for e-commerce platforms.

scholarly journals Organising to beat the Trade Union Act (2016) voting thresholds: a case study of organising and tactics from the University and College Union

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
James Richards ◽  
Vaughan Ellis
Keyword(s):  
Trade Union ◽  
Trade Unions ◽  
Best Practice ◽  
Content Type ◽  
Theoretical Contribution ◽  
Proposed Model ◽  
College Union ◽  
The University ◽  
Further Development

PurposeA retrospective action-research case study of one branch of the University and College Union (UCU) is used to show how threshold requirements of the Act can be systematically beaten.Design/methodology/approachThe paper responds to calls for “best practice” on how trade unions may react to member voting threshold requirements of the Trade Union Act 2016 (the Act). A broader aim is to make a theoretical contribution related to trade union organising and tactics in “get the vote out” (GTVO) industrial action organising campaigns.FindingsFindings are presented as a lead organiser's first-hand account of a successful GTVO campaign contextualised in relation to theories of organising. The findings offer “best practice” for union organisers required to beat the Act's voting thresholds and also contribute to theories surrounding trade union organising tactics.Research limitations/implicationsFurther development and adaptation of the proposed model may be required when applied to larger bargaining units and different organising contexts.Practical implicationsThe findings can inform the organising practices/tactics of trade unions in relation to statutory ballots. The findings also allow Human Resource (HR) practitioners to reflect on their approach to dealing with unions capable of mounting successful GTVO campaigns.Social implicationsThe findings have the potential to collectively empower workers, via their trade unions, to defend and further their interests in a post-financial crisis context and in the shadow of the Covid-19 pandemic.Originality/valueThis is the first known empirical account of organising to exceed voting thresholds of the Act, providing practical steps for union organisers in planning for statutory ballots. Further value lies in the paper's use of a novel first-hand account of a GTVO campaign, offering a new and first, theoretical model of organising tactics to beat the Act.

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