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Article
Publication date: 15 December 2017

Farshid Abdi, Kaveh Khalili-Damghani and Shaghayegh Abolmakarem

Customer insurance coverage sales plan problem, in which the loyal customers are recognized and offered some special plans, is an essential problem facing insurance…

Abstract

Purpose

Customer insurance coverage sales plan problem, in which the loyal customers are recognized and offered some special plans, is an essential problem facing insurance companies. On the other hand, the loyal customers who have enough potential to renew their insurance contracts at the end of the contract term should be persuaded to repurchase or renew their contracts. The aim of this paper is to propose a three-stage data-mining approach to recognize high-potential loyal insurance customers and to predict/plan special insurance coverage sales.

Design/methodology/approach

The first stage addresses data cleansing. In the second stage, several filter and wrapper methods are implemented to select proper features. In the third stage, K-nearest neighbor algorithm is used to cluster the customers. The approach aims to select a compact feature subset with the maximal prediction capability. The proposed approach can detect the customers who are more likely to buy a specific insurance coverage at the end of a contract term.

Findings

The proposed approach has been applied in a real case study of insurance company in Iran. On the basis of the findings, the proposed approach is capable of recognizing the customer clusters and planning a suitable insurance coverage sales plans for loyal customers with proper accuracy level. Therefore, the proposed approach can be useful for the insurance company which helps them to identify their potential clients. Consequently, insurance managers can consider appropriate marketing tactics and appropriate resource allocation of the insurance company to their high-potential loyal customers and prevent switching them to competitors.

Originality/value

Despite the importance of recognizing high-potential loyal insurance customers, little study has been done in this area. In this paper, data-mining techniques were developed for the prediction of special insurance coverage sales on the basis of customers’ characteristics. The method allows the insurance company to prioritize their customers and focus their attention on high-potential loyal customers. Using the outputs of the proposed approach, the insurance companies can offer the most productive/economic insurance coverage contracts to their customers. The approach proposed by this study be customized and may be used in other service companies.

Article
Publication date: 4 February 2022

Arezoo Gazori-Nishabori, Kaveh Khalili-Damghani and Ashkan Hafezalkotob

A Nash bargaining game data envelopment analysis (NBG-DEA) model is proposed to measure the efficiency of dynamic multi-period network structures. This paper aims to…

Abstract

Purpose

A Nash bargaining game data envelopment analysis (NBG-DEA) model is proposed to measure the efficiency of dynamic multi-period network structures. This paper aims to propose NBG-DEA model to measure the performance of decision-making units with complicated network structures.

Design/methodology/approach

As the proposed NBG-DEA model is a non-linear mathematical programming, finding its global optimum solution is hard. Therefore, meta-heuristic algorithms are used to solve non-linear optimization problems. Fortunately, the NBG-DEA model optimizes the well-formed problem, so that it can be solved by different non-linear methods including meta-heuristic algorithms. Hence, a meta-heuristic algorithm, called particle swarm optimization (PSO) is proposed to solve the NBG-DEA model in this paper. The case study is Industrial Management Institute (IMI), which is a leading organization in providing consulting management, publication and educational services in Iran. The sub-processes of IMI are considered as players where their pay-off is defined as the efficiency of sub-processes. The network structure of IMI is studied during multiple periods.

Findings

The proposed NBG-DEA model is applied to measure the efficiency scores in the IMI case study. The solution found by the PSO algorithm, which is implemented in MATLAB software, is compared with that generated by a classic non-linear method called gradient descent implemented in LINGO software.

Originality/value

The experiments proved that suitable and feasible solutions could be found by solving the NBG-DEA model and shows that PSO algorithm solves this model in reasonable central process unit time.

Details

Journal of Modelling in Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1746-5664

Keywords

Article
Publication date: 9 November 2018

Nasser Javid, Kaveh Khalili-Damghani, Ahmad Makui and Farshid Abdi

This paper aims to propose a multi-dimensional model on the basis of the key factors of the flexibility and the complexity through structural equation modeling (SEM)…

Abstract

Purpose

This paper aims to propose a multi-dimensional model on the basis of the key factors of the flexibility and the complexity through structural equation modeling (SEM). Dimensions of the flexibilities and complexity, including 16 main factors and 34 sub-factors, are investigated. The sampling of the research is accomplished using both academic and industrial experts.

Design/methodology/approach

A huge electronic questionnaire analysis, including 1,250 samples from which 1,036 were returned, was accomplished in various universities and manufacturing companies throughout the USA, Europe and Asia. Partial least square-SEM (PLS-SEM) is used to test the hypotheses through confirmatory factor analysis.

Findings

The results reveal insightful information about the impacts of different dimensions of flexibility on each other and also the effect of the flexibility on the complexity. Finally, system of linear mathematical equations for flexibility-complexity trade-off is proposed. This can be applied to realize the trade-off among dimensions of flexibility and complexity.

Originality/value

Flexible manufacturing systems are formed to meet the needs of the customers. Such systems try to produce products in appropriate quality at the right time and at the specified quantity. These, in turn, require flexibility and will cause complexity. Although flexibility and complexity are both important, there is no comprehensive framework in which the multi-dimensional relationships of the manufacturing flexibility and complexity, as well as their dimensions, are demonstrated.

Article
Publication date: 8 April 2021

Amir Farmahini Farahani, Hosein Didehkhani, Kaveh Khalili-Damghani, Amir Homayoun Sarfaraz and Mehdi Hajirezaie

This study aims to investigate the interactive network of risk factors in the construction and preparation project of gas condensate storage tanks in the presence of sanctions.

Abstract

Purpose

This study aims to investigate the interactive network of risk factors in the construction and preparation project of gas condensate storage tanks in the presence of sanctions.

Design/methodology/approach

First, this paper determines and weighs the project goals using the stepwise weight assessment ratio analysis method. Then, this study identifies and categorizes the project risks and form the network of the project risk factors based on the weight of the project goals by using interpretive structural modeling and decision-making trial and evaluation laboratory techniques.

Findings

The results of the current work divide the risks of such projects into five financial, technical, managerial and contractual, social and environmental and political categories. The analyzes indicate the complicated risk network and the cause-and-effect interactions between the risks. The findings identify the financial and political risk clusters as the most effective category and select the technical, managerial and contractual and social and environmental risk clusters as the most affected categories. The technical risk has the least important among the others under the sanction conditions.

Originality/value

This paper model the domino effect of the risk factors considering the complicated interactions and the cause-and-effect relations in a network. Moreover, this study discusses the importance of the risk factors in oil and gas megaprojects in the presence of sanctions. Finally, this paper applies the proposed approach to a real case study in the field of gas projects.

Details

Journal of Modelling in Management, vol. 17 no. 2
Type: Research Article
ISSN: 1746-5664

Keywords

Article
Publication date: 8 May 2018

Mina Moeinedini, Sadigh Raissi and Kaveh Khalili-Damghani

Enterprise resource planning (ERP) is assumed as a commonly used solution in order to provide an integrated view of core business processes, including product planning…

Abstract

Purpose

Enterprise resource planning (ERP) is assumed as a commonly used solution in order to provide an integrated view of core business processes, including product planning, manufacturing cost, delivery, marketing, sales, inventory management, shipping and payment. Selection and implementation of a suitable ERP solution are not assumed a trivial project because of the challenging nature of it, high costs, long-duration of installation and customization, as well as lack of successful benchmarking experiences. During the ERP projects, several risk factors threat the successful implementation of the project. These risk factors usually refer to different phases of the ERP projects including purchasing, pilot implementation, teaching, install, synchronizing, and movement from old systems toward new ones, initiation and utilization. These risk factors have dominant effects on each other. The purpose of this paper is to explore the hybrid reliability-based method is proposed to assess the risk factors of ERP solutions.

Design/methodology/approach

In this regard, the most important risk factors of ERP solutions are first determined. Then, the interactive relations of these factors are recognized using a graph based method, called interpretive structural modeling. The resultant network of relations between these factors initiates a new viewpoint toward the cause and effect relations among risk factors. Afterwards, a fuzzy fault tree analysis is proposed to calculate Failure Fuzzy Possibility (FFP) for the basic events of the fault tree leading to a quantitative evaluation of risk factors.

Findings

The whole proposed method is applied in a well-known Iranian foodservice distributor as a case study. The most impressive risk factors are identified, classified and prioritized. Moreover, the cause and effect diagram between the risk factors are identified. So, the ERP leader can plan a low-risk project and increase the chance of success.

Originality/value

According to the authors’ best knowledge, such approach was not reported before in the literature of ERP risk assessments.

Details

International Journal of Quality & Reliability Management, vol. 35 no. 5
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 6 September 2021

Bahareh Shafipour-Omrani, Alireza Rashidi Komijan, Seyed Jafar Sadjadi, Kaveh Khalili-Damghani and Vahidreza Ghezavati

One of the main advantages of the proposed model is that it is flexible to generate n-day pairings simultaneously. It means that, despite previous researches, one-day to n

Abstract

Purpose

One of the main advantages of the proposed model is that it is flexible to generate n-day pairings simultaneously. It means that, despite previous researches, one-day to n-day pairings can be generated in a single model. The flexibility in generating parings causes that the proposed model leads to better solutions compared to existing models. Another advantage of the model is minimizing the risk of COVID-19 by limitation of daily flights as well as elapsed time minimization. As airports are among high risk places in COVID-19 pandemic, minimization of infection risk is considered in this model for the first time. Genetic algorithm is used as the solution approach, and its efficiency is compared to GAMS in small and medium-size problems.

Design/methodology/approach

One of the most complex issues in airlines is crew scheduling problem which is divided into two subproblems: crew pairing problem (CPP) and crew rostering problem (CRP). Generating crew pairings is a tremendous and exhausting task as millions of pairings may be generated for an airline. Moreover, crew cost has the largest share in total cost of airlines after fuel cost. As a result, crew scheduling with the aim of cost minimization is one of the most important issues in airlines. In this paper, a new bi-objective mixed integer programming model is proposed to generate pairings in such a way that deadhead cost, crew cost and the risk of COVID-19 are minimized.

Findings

The proposed model is applied for domestic flights of Iran Air airline. The results of the study indicate that genetic algorithm solutions have only 0.414 and 0.380 gap on average to optimum values of the first and the second objective functions, respectively. Due to the flexibility of the proposed model, it improves solutions resulted from existing models with fixed-duty pairings. Crew cost is decreased by 12.82, 24.72, 4.05 and 14.86% compared to one-duty to four-duty models. In detail, crew salary is improved by 12.85, 24.64, 4.07 and 14.91% and deadhead cost is decreased by 11.87, 26.98, 3.27, and 13.35% compared to one-duty to four-duty models, respectively.

Originality/value

The authors confirm that it is an original paper, has not been published elsewhere and is not currently under consideration of any other journal.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 26 June 2020

Hesam Adarang, Ali Bozorgi-Amiri, Kaveh Khalili-Damghani and Reza Tavakkoli-Moghaddam

This paper addresses a location-routing problem (LRP) under uncertainty for providing emergency medical services (EMS) during disasters, which is formulated using a robust…

Abstract

Purpose

This paper addresses a location-routing problem (LRP) under uncertainty for providing emergency medical services (EMS) during disasters, which is formulated using a robust optimization (RO) approach. The objectives consist of minimizing relief time and the total cost including location costs and the cost of route coverage by the vehicles (ambulances and helicopters).

Design/methodology/approach

A shuffled frog leaping algorithm (SFLA) is developed to solve the problem and the performance is assessed using both the ε-constraint method and NSGA-II algorithm. For a more accurate validation of the proposed algorithm, the four indicators of dispersion measure (DM), mean ideal distance (MID), space measure (SM), and the number of Pareto solutions (NPS) are used.

Findings

The results obtained indicate the efficiency of the proposed algorithm within a proper computation time compared to the CPLEX solver as an exact method.

Research limitations/implications

In this study, the planning horizon is not considered in the model which can affect the value of parameters such as demand. Moreover, the uncertain nature of the other parameters such as traveling time is not incorporated into the model.

Practical implications

The outcomes of this research are helpful for decision-makers for the planning and management of casualty transportation under uncertain environment. The proposed algorithm can obtain acceptable solutions for real-world cases.

Originality/value

A novel robust mixed-integer linear programming (MILP) model is proposed to formulate the problem as a LRP. To solve the problem, two efficient metaheuristic algorithms were developed to determine the optimal values of objectives and decision variables.

Details

Journal of Humanitarian Logistics and Supply Chain Management, vol. 10 no. 3
Type: Research Article
ISSN: 2042-6747

Keywords

Article
Publication date: 9 May 2016

Maedeh Rezaeisaray, Sadoullah Ebrahimnejad and Kaveh Khalili-Damghani

The purpose of this paper is to determine the criteria weights of outsourcing and their key role in ranking outsourcing suppliers.

Abstract

Purpose

The purpose of this paper is to determine the criteria weights of outsourcing and their key role in ranking outsourcing suppliers.

Design/methodology/approach

A new hybrid multi-criteria decision-making approach merges three tools, namely, decision making trial and evaluation (DEMATLE), fuzzy analytic network process (FANP) and ordinal/cardinal data envelopment analysis (DEA) model. Afterwards, experts’ opinions were gathered from a Pipe and Fittings company. Finally, their opinions were incorporated in three-stage approach for outsourcing suppliers’ selection.

Findings

The findings of this study show that among the selective criteria for outsourcing, business development, focus on basic activities and order delays are the three most important criteria. Also, the proposed approach ranks suppliers to facilitate decision making for selection.

Research limitations/implications

The number of suppliers, selection criteria and the number of members of the respondents’ team have been identified as some of the limitations of the present study.

Practical implications

The study has significant and practical implications for the managers and for the organizations which have to choose top suppliers, particularly in the case of dealing with numerous and qualitative/quantitative criteria.

Originality/value

This paper proposed a new three-stage approach that incorporates outputs of previous as inputs of next stage to increasing results accuracy. Also, it showed that by incorporating results of FANP method into DEA model, key role of experts’ opinions as a qualitative and quantitative criteria can be caused by increasing flexibility of decision process.

Details

Journal of Modelling in Management, vol. 11 no. 2
Type: Research Article
ISSN: 1746-5664

Keywords

Article
Publication date: 16 May 2019

Abhilasha Panwar, Kamalendra Kumar Tripathi and Kumar Neeraj Jha

The purpose of this paper is to develop a qualitative framework for the selection of the most appropriate optimization algorithm for the multi-objective trade-off problem…

Abstract

Purpose

The purpose of this paper is to develop a qualitative framework for the selection of the most appropriate optimization algorithm for the multi-objective trade-off problem (MOTP) in construction projects based on the predefined performance parameters.

Design/methodology/approach

A total of 6 optimization algorithms and 13 performance parameters were identified through literature review. The experts were asked to indicate their preferences between each pair of optimization algorithms and performance parameters. A multi-criteria decision-making tool, namely, consistent fuzzy preference relation was applied to analyze the responses of the experts. The results from the analysis were applied to evaluate their relative weights which were used to provide a ranking to the algorithms.

Findings

This study provided a qualitative framework which can be used to identify the most appropriate optimization algorithm for the MOTP beforehand. The outcome suggested that non-dominated sorting genetic algorithm (NSGA) was the most appropriate algorithm whereas linear programming was found to be the least appropriate for MOTPs.

Originality/value

The devised framework may provide a useful insight for the construction practitioners to choose an effective optimization algorithm tool for preparing an efficient project schedule aiming toward the desired optimal improvement in achieving the various objectives. Identification of the absolute best optimization algorithm is very difficult to attain due to various problems such as the inherent complexities and intricacies of the algorithm and different class of problems. However, the devised framework offers a primary insight into the selection of the most appropriate alternative among the available algorithms.

Details

Engineering, Construction and Architectural Management, vol. 26 no. 9
Type: Research Article
ISSN: 0969-9988

Keywords

Article
Publication date: 21 February 2020

Farhad Hosseinzadeh, Behzad Paryzad, Nasser Shahsavari Pour and Esmaeil Najafi

The optimization and tradeoff of cost-time-quality-risk in one dimension and this four-dimensional problem in ambiguous mode and risk can be neither predicted nor…

Abstract

Purpose

The optimization and tradeoff of cost-time-quality-risk in one dimension and this four-dimensional problem in ambiguous mode and risk can be neither predicted nor estimated. This study aims to solve this problem and rank fuzzy numbers using an innovative algorithm “STHD” and a special technique “radius of gyration” (ROG) for fuzzy answers, respectively.

Design/methodology/approach

First, it is the optimization of a fully fuzzy four-dimensional problem which has never been dealt with in regard to risk in ambiguous mode and complexities. Therefore, the risk is a parameter which has been examined neither in probability and estimableness mode nor in the ambiguous mode so far. Second, it is a fully fuzzy tradeoff which, based on the principle of incompatibility “Zadeh, 1973”, proposes that when the complexity of a system surpasses the limited point, it becomes impossible to define the performance of that system accurately, precisely and meaningfully. The authors believe that this principle is the source of fuzzy logic. Third, for calculating and ranking fuzzy numbers of answers, a special technique for fuzzy numbers has been used. Fourth, For the sake of ease, precision and efficiency, an innovative algorithm called the technique of hunting dolphins “STHD” has been used. Finally, the problem is very close to reality. By applying risk in ambiguous mode, the problem has been realistically looked at.

Findings

The results showed that the algorithm was highly robust, with its performance depending very little on the regulation of the parameters. Ranking fuzzy numbers using the ROG indicated the flexibility of fuzzy logic, and it was also determined that the most appropriate regulations were to ensure low time, risk and cost but maximum quality in calculations, which were produced non-uniformly based on the levels of Pareto answers.

Originality/value

The ROG and Chanas Fuzzy Critical Path Method as developed by other researchers have been used. Despite the increase in limitations, parameters can develop. The originality of this study with regard to evaluating the results of tradeoff combinatorial optimization is upon decision-making which has a special and highly strategic role in the fate of the project, with the research been conducted with a special approach and different tools in a fully fuzzy environment.

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