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1 – 10 of over 3000Akhilesh Kumar, Gaurav Kumar, Tanaya Vijay Ramane and Gurjot Singh
This study proposes strategies for vaccine center allocation for coronavirus disease (COVID) vaccine by determining the number of vaccination stations required for the vaccination…
Abstract
Purpose
This study proposes strategies for vaccine center allocation for coronavirus disease (COVID) vaccine by determining the number of vaccination stations required for the vaccination drive, location of vaccination station, assignment of demand group to vaccination station, allocation of the scarce medical professional teams to station and number of optimal days a vaccination station to be functional in a week.
Design/methodology/approach
The authors propose a mixed-integer nonlinear programming model. However, to handle nonlinearity, the authors devise a heuristic and then propose a two-stage mixed-integer linear programming (MILP) formulation to optimize the allocation of vaccination centers or stations to demand groups in the first stage and the allocation of vaccination centers to cold storage links in the second stage. The first stage optimizes the cost and average distance traveled by people to reach the vaccination center, whereas the second stage optimizes the vaccine’s holding and storage and transportation cost by efficiently allocating cold storage links to the centers.
Findings
The model is studied for the real-world case of Chandigarh, India. The results obtained validate that the proposed approach can immensely help government agencies and policymaking body for a successful vaccination drive. The model tries to find a tradeoff between loss due to underutilized medical teams and the distance traveled by a demand group to get the vaccination.
Originality/value
To the best of our knowledge, there are hardly any studies on a vaccination program at such a scale due to sudden outbreaks such as Covid-19.
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Pouyan Mahdavi-Roshan and Seyed Meysam Mousavi
Most projects are facing delays, and accelerating the pace of project progress is a necessity. Project managers are responsible for completing the project on time with minimum…
Abstract
Purpose
Most projects are facing delays, and accelerating the pace of project progress is a necessity. Project managers are responsible for completing the project on time with minimum cost and with maximum quality. This study provides a trade-off between time, cost, and quality objectives to optimize project scheduling.
Design/methodology/approach
The current paper presents a new resource-constrained multi-mode time–cost–quality trade-off project scheduling model with lags under finish-to-start relations. To be more realistic, crashing and overlapping techniques are utilized. To handle uncertainty, which is a source of project complexity, interval-valued fuzzy sets are adopted on several parameters. In addition, a new hybrid solution approach is developed to cope with interval-valued fuzzy mathematical model that is based on different alpha-levels and compensatory methods. To find the compatible solution among conflicting objectives, an arithmetical average method is provided as a compensatory approach.
Findings
The interval-valued fuzzy sets approach proposed in this paper is denoted to be scalable, efficient, generalizable and practical in project environments. The results demonstrated that the crashing and overlapping techniques improve time–cost–quality trade-off project scheduling model. Also, interval-valued fuzzy sets can properly manage expressions of the uncertainty of projects which are realistic and practical. The proposed mathematical model is validated by solving a medium-sized dataset an adopted case study. In addition, with a sensitivity analysis approach, the solutions are compared and the model performance is confirmed.
Originality/value
This paper introduces a new continuous-based, resource-constrained, and multi-mode model with crashing and overlapping techniques simultaneously. In addition, a new hybrid compensatory solution approach is extended based on different alpha-levels to handle interval-valued fuzzy multi-objective mathematical model of project scheduling with influential uncertain parameters.
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Hamid Asnaashari, Abbas Sheikh Aboumasoudi, Mohammad Reza Mozaffari and Mohammad Reza Feylizadeh
The application of correct contractor selection strategies leads to the selection of a qualified contractor and, as a result, the on-time delivery of the project with the desired…
Abstract
Purpose
The application of correct contractor selection strategies leads to the selection of a qualified contractor and, as a result, the on-time delivery of the project with the desired quality and within the predetermined budgetary constraints. For this reason, evaluating and qualifying contractors before reviewing the proposed prices has been considered an important issue. One factor that disrupts the project completion process and the failure to achieve pre-planned goals effectively is the occurrence of contractors' disputes and claims in projects. To this end, the present study explores claim-reduction strategies for selecting effective contractors in an uncertain environment to reduce possible problems.
Design/methodology/approach
The two-step grey data envelopment analysis (GDEA) approach was used to measure efficiency as a powerful tool in selecting efficient contractors during tenders. This approach can extend the applications of multi-criteria decision-making (MCDM) models. In other words, given some uncertainties, the unavailability of some data, and the problems with the DEA model, the two-step GDEA model was used to rank the contractors. The data confirmed the satisfactory outcomes from the selected model.
Findings
The preliminary assessment of contractors is a pre-tendering process and a step in categorizing contractors, excluding contractors lacking required qualifications, and selecting efficient contractors. At first, it will help the employer to exclude inexperienced and unqualified contractors, save resources and time, reduce threats, replace opportunities with threats, and reduce material and non-material costs during the completion of the project until the projects are put into operation. Consequently, this approach reduces claims to a minimum level and increases the organization's effective material and non-material profit.
Originality/value
Oil and gas plans and projects have a significant, sensitive, and decisive role in the economic, social, political, cultural, infrastructural, and all-round development of Iran; This is while most of the financial resources needed to implement the development and programs across the country come from oil revenues. Studies have indicated that despite the importance of these plans and projects, many of them are not completed successfully, and this causes irreparable losses to the country's economy and development in various fields.
Highlight
The findings of this study can be used by organizations to select more effective contractors to assign projects and plans to them.
The preliminary assessment of contractors is a pre-tendering process and a step in categorizing contractors, excluding contractors who lack required qualifications, and finally selecting efficient contractors.
At first, it will help the employer to exclude inexperienced and unqualified contractors, save resources and time, reduce threats, replace opportunities with threats, and reduce material and non-material costs during the completion of the project until the projects are put into operation.
This approach also gives credit to the employer during the execution period and contributes to assessing unqualified contractors and reducing the temptation to hand over the project to an unqualified contractor but with a lower bid price.
Consequently, this approach reduces claims to a minimum level and increases the effective material and non-material profit of the organization.
Moreover, it provides an extra-organizational evaluation for contractors, motivating them to upgrade their capabilities and optimally allocate material and non-material resources, especially human resources.
The findings of this study can be used by organizations to select more effective contractors to assign projects and plans to them.
The preliminary assessment of contractors is a pre-tendering process and a step in categorizing contractors, excluding contractors who lack required qualifications, and finally selecting efficient contractors.
At first, it will help the employer to exclude inexperienced and unqualified contractors, save resources and time, reduce threats, replace opportunities with threats, and reduce material and non-material costs during the completion of the project until the projects are put into operation.
This approach also gives credit to the employer during the execution period and contributes to assessing unqualified contractors and reducing the temptation to hand over the project to an unqualified contractor but with a lower bid price.
Consequently, this approach reduces claims to a minimum level and increases the effective material and non-material profit of the organization.
Moreover, it provides an extra-organizational evaluation for contractors, motivating them to upgrade their capabilities and optimally allocate material and non-material resources, especially human resources.
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Amir Yaqoubi, Fatemeh Sabouhi, Ali Bozorgi-Amiri and Mohsen Sadegh Amalnick
A growing body of evidence points to the influence of location and allocation decisions on the structure of healthcare networks. The authors introduced a three-level hierarchical…
Abstract
Purpose
A growing body of evidence points to the influence of location and allocation decisions on the structure of healthcare networks. The authors introduced a three-level hierarchical facility location model to minimize travel time in the healthcare system under uncertainty.
Design/methodology/approach
Most healthcare networks are hierarchical and, as a result, the linkage between their levels makes it difficult to specify the location of the facilities. In this article, the authors present a hybrid approach according to data envelopment analysis and robust programming to design a healthcare network. In the first phase, the efficiency of each potential location is calculated based on the non-radial range-adjusted measure considering desirable and undesirable outputs based on a number of criteria such as the target area's population, proximity to earthquake faults, quality of urban life, urban decrepitude, etc. The locations deemed suitable are then used as candidate locations in the mathematical model. In the second phase, based on the proposed robust optimization model, called light robustness, the location and allocation decisions are adopted.
Findings
The developed model is evaluated using an actual-world case study in District 1 of Tehran, Iran and relevant results and different sensitivity analyses were presented as well. When the percentage of referral parameters changes, the value of the robust model's objective function increases.
Originality/value
The contributions of this article are listed as follows: Considering desirable and undesirable criteria to selecting candidate locations, providing a robust programming model for building a service network and applying the developed model to an actual-world case study.
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Fatemeh Yazdani, Mehdi Khashei and Seyed Reza Hejazi
This paper aims to detect the most profitable, i.e. optimal turning points (TPs), from the history of time series using a binary integer programming (BIP) model. TPs prediction…
Abstract
Purpose
This paper aims to detect the most profitable, i.e. optimal turning points (TPs), from the history of time series using a binary integer programming (BIP) model. TPs prediction problem is one of the most popular yet challenging topics in financial planning. Predicting profitable TPs results in earning profit by offering the opportunity to buy at low and selling at high. TPs detected from the history of time series will be used as the prediction model’s input. According to the literature, the predicted TPs’ profitability depends on the detected TPs’ profitability. Therefore, research for improving the profitability of detection methods has been never given up. Nevertheless, to the best of our knowledge, none of the existing methods can detect the optimal TPs.
Design/methodology/approach
The objective function of our model maximizes the profit of adopting all the trading strategies. The decision variables represent whether or not to detect the breakpoints as TPs. The assumptions of the model are as follows. Short-selling is possible. The time value for the money is not considered. Detection of consecutive buying (selling) TPs is not possible.
Findings
Empirical results with 20 data sets from Shanghai Stock Exchange indicate that the model detects the optimal TPs.
Originality/value
The proposed model, in contrast to the other methods, can detect the optimal TPs. Additionally, the proposed model, in contrast to the other methods, requires transaction cost as its only input parameter. This advantage reduces the process’ calculations.
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Vimal K.E.K., Sonu Raja, Venkata Siva Prasanth Yendeti, Amarendra Kancharla and Jayakrishna Kandasamy
The purpose of this paper is to investigate the effect of current carbon tax (CT) policy on organizations involved in a sharing network relation.
Abstract
Purpose
The purpose of this paper is to investigate the effect of current carbon tax (CT) policy on organizations involved in a sharing network relation.
Design/methodology/approach
For finding the CT and economic value of the industries connected in a sharing network model a multi-objective multi-integer linear model has been formulated. The data set of the case organization is used for computation. The formulated mathematical model is computed with the aid of GAMS optimization program.
Findings
This research paper demonstrates the effectiveness of the sharing network strategy in increasing the economic value and decreasing the CT for industries involved in sharing network. The CT value INR 3,012.694 for the industries in Scenario II which incorporates the sharing network is less than the CT INR 3,580.167 for industries in Scenario I without sharing network.
Research limitations/implications
The data used for the computation is based on a particular sharing network under investigation. The formulated mathematical model can be checked with similar sharing networks by varying the parameters.
Practical implications
This work can aid in gaining complete knowledge on the sharing network strategy which can uplift the resources and the monetary value of the non-efficient industries moving them towards sustainable and greener supply chain practices.
Social implications
The presented work can impact various industries in developing countries providing them with a strategy to enhance their resources and economic value by maintaining an amicable relation.
Originality/value
This work uniquely was able to validate economic feasibility and CT in accordance with the carbon footprint involved in sharing network. This sharing network also incorporates the concepts of circular economy and reverse logistics for showcasing a better strategy.
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Behzad Paryzad and Kourosh Eshghi
This paper aims to conduct a fuzzy discrete time cost quality risk in the ambiguous mode CO2 tradeoff problem (FDTCQRP*TP) in a megaproject based on fuzzy ground.
Abstract
Purpose
This paper aims to conduct a fuzzy discrete time cost quality risk in the ambiguous mode CO2 tradeoff problem (FDTCQRP*TP) in a megaproject based on fuzzy ground.
Design/methodology/approach
A combinatorial evolutionary algorithm using Fuzzy Invasive Weed Optimization (FIWO) is used in the discrete form of the problem where the parameters are fully fuzzy multi-objective and provide a space incorporating all dimensions of the problem. Also, the fuzzy data and computations are used with the Chanas method selected for the computational analysis. Moreover, uncertainty is defined in FIWO. The presented FIWO simulation, its utility and superiority are tested on sample problems.
Findings
The reproduction, rearrangement and maintaining elite invasive weeds in FIWO can lead to a higher level of accuracy, convergence and strength for solving FDTCQRP*TP fuzzy rules and a risk ground in the ambiguous mode with the emphasis on the necessity of CO2 pollution reduction. The results reveal the effectiveness of the algorithm and its flexibility in the megaproject managers' decision making, convergence and accuracy regarding CO2 pollution reduction.
Originality/value
This paper offers a multi-objective fully fuzzy tradeoff in the ambiguous mode with the approach of CO2 pollution reduction.
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Varun Mahajan, Sandeep Kumar Mogha and R.K.Pavan Kumar Pannala
The main purpose of this paper is to determine the bias-corrected efficiencies and rankings of the selected hotels and restaurants (H&Rs) in India.
Abstract
Purpose
The main purpose of this paper is to determine the bias-corrected efficiencies and rankings of the selected hotels and restaurants (H&Rs) in India.
Design/methodology/approach
The data for the Indian H&R sector are collected from the Prowess database. The bootstrap data envelopment analysis (DEA) based on a constant return to scale (CRS), variable return to scale-input oriented (VRS-IP) and variable return to scale-output oriented (VRS-OP) are applied on H&Rs to obtain the bias-corrected efficiencies.
Findings
It is found that relative efficiencies using basic DEA methods of all the 45 H&Rs of India are overestimated. These efficiencies are corrected using bias correction through bootstrap DEA methods. The bounds for the efficiencies of each H&R are computed using all the adopted methods. All H&Rs are ranked using bias-corrected efficiencies, and the linear trend between ranks suggests that the H&Rs are ranked almost similarly by all the adopted methods.
Practical implications
To improve efficiency, Indian H&R companies must rethink their personnel needs by enhancing their workforce management capabilities. The government needs to extend more support to this sector by introducing a liberal legislation framework and supporting infrastructure policies.
Originality/value
There is a paucity of studies on H&Rs in India. The current study focused on measuring bias-corrected efficiencies of the selected H&Rs of India. This study is one of the few initiatives to explore bias-corrected efficiencies extensively using the bootstrap DEA method.
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Keywords
Rahmi Yuniarti, Ilyas Masudin, Ahmad Rusdiansyah and Dwi Iryaning Handayani
This study aimed to develop the integration of the multiperiod production-distribution model in a closed-loop supply chain involving carbon emission and traceability. The…
Abstract
Purpose
This study aimed to develop the integration of the multiperiod production-distribution model in a closed-loop supply chain involving carbon emission and traceability. The developed model was for agricultural food (agri-food) products, considering the reverse flow of food waste from the disposal center (composting center) to producers.
Findings
The results indicate that integrating the production and distribution model considering food waste recycling provides low carbon emissions in lower total costs. The sensitivity analysis also found that there are trade-offs between production and distribution rate and food waste levels on carbon emission and traceability.
Research limitations/implications
This study focuses on the mathematical modeling of a multiperiod production-distribution formulation for a closed-loop supply chain.
Originality/value
The model of the agri-food closed-loop supply chain in this study that considers food recycling and carbon emissions would help stakeholders involved in the agri-food supply chain to reduce food waste and carbon emissions.
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Gokhan Agac, Birdogan Baki and Ilker Murat Ar
The purpose of this study is to systematically review the existing literature on the blood supply chain (BSC) from a network design perspective and highlight the research gaps in…
Abstract
Purpose
The purpose of this study is to systematically review the existing literature on the blood supply chain (BSC) from a network design perspective and highlight the research gaps in this area. Moreover, it also aims to pinpoint new research opportunities based on the recent innovative technologies for the BSC network design.
Design/methodology/approach
The study gives a comprehensive systematic review of the BSC network design studies until October 2021. This review was carried out in accordance with preferred reporting items for systematic reviews and meta-analyses (PRISMA). In the literature review, a total of 87 studies were analyzed under six main categories as model structure, application model, solution approach, problem type, the parties of the supply chain and innovative technologies.
Findings
The results of the study present the researchers’ tendencies and preferences when designing their BSC network models.
Research limitations/implications
The study presents a guide for researchers and practitioners on BSC from the point of view of network design and encourages adopting innovative technologies in their BSC network designs.
Originality/value
The study provides a comprehensive systematic review of related studies from the BSC network design perspective and explores research gaps in the collection and distribution processes. Furthermore, it addresses innovative research opportunities by using innovative technologies in the area of BSC network design.
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