Khodakaram Salimifard | PGU - Academia.edu (original) (raw)

Papers by Khodakaram Salimifard

Annals of Operations Research

To provide health services, hospitals consume electrical power and contribute to the CO2 emission... more To provide health services, hospitals consume electrical power and contribute to the CO2 emission. This paper aims to develop a modelling approach to optimize hospital services while reducing CO2 emissions. To capture treatment processes and the production of carbon dioxide, a hybrid method of data mining and simulation–optimization techniques is proposed. Different clustering algorithms are used to categorize patients. Using quality indicators, clustering methods are evaluated to find the best cluster sets, and then patients are categorized accordingly. Discrete-event simulation is applied to each patient category to estimate performance measures such as number of patients being served, waiting times, and length of stay, as well as the amount of CO2 emission. To optimize performance measures of patient flow, metaheuristic searches have been used. The dataset of Bushehr Heart Hospital is considered as a case study. Based on K-means, K-medoid, Hierarchical clustering, and Fuzzy C-mea...

Mudīriyyat-i ṣan̒atī, 2013

University course timetabling is a complex optimizationproblem. There are many components like de... more University course timetabling is a complex optimizationproblem. There are many components like departments, faculties, rooms,and students making the problem huge and difficult to solve. Eachcomponent enforces a set of normally conflicting constraints on thesolution space. The problem will be solved if courses are scheduled indifferent rooms and within some specific time slots such that a set ofconstraints are satisfied. In this paper, a graph-based hyper-heuristic isproposed to find a solution to the problem. This is a two tiers modelingapproach combining hyper heuristic with graph coloring technique. Theupper tier heuristic is used to select a suitable heuristic to find a feasiblesolution on the lower tier. To find the suitability of the proposedapproach, it has been applied to a real world case. The proposed approachwas able to satisfy all the hard and soft constraints. Based on the researchfindings, it can be concluded that a graph-based hyper heuristic approachis a suitable and ...

Taḥqīqāt-i mālī, 2016

Morkowitz model is one of the well-known models in portfolio selection problem. This paper presen... more Morkowitz model is one of the well-known models in portfolio selection problem. This paper presents an extended version of Markowitz mean semi variance portfolio selection model. The extended model considers sets of constraints including cardinality, bounds on holdings, sector capitalization, an entropy constraints. It also considers transaction costs. The problem model has a combinatorial structure. Due to the NP-hard characteristic of the resulting mathematical model, Harmony Search Meta-heuristic algorithm was used to solve the model. Since the proposed mathematical model is a multi-objective one, the Pareto solution approach was applied. To investigate the applicability of the proposed model, a data set of ten stocks from Tehran Stock Exchange, from March 2011 to December 2015, is used as a case study. The obtained efficient frontier indicates the applicability of the harmony algorithm in the optimization model. Research results show that the proposed model is efficiently is cap...

Journal of Information Technology Management, 2015

In the wake of rapid growth in information technology, modern organizations seeking to increase t... more In the wake of rapid growth in information technology, modern organizations seeking to increase the access and exchange data with minimal costs. BYOD is an emergent policy under which employees are allowed to use their personal devices such as smart phones, tablets and laptops to perform tasks. In this study, a model to prioritize the factors influencing the organizational adoption of BYOD is proposed. The model has two main criteria, each of which has ten subcriteria. Using ICT experts' views and Improved Fuzzy Analytical Hierarchy Process technique, the model criteria were weighted. The two main factors, political factors identified as foremost important factor and behavioral intention to use IT were in the second priority. The model can be used as a basis for further research and successful implementation of BYOD by the organizations.

Applied Intelligence, 2020

Parallel machine scheduling is one of the most common studied problems in recent years, however, ... more Parallel machine scheduling is one of the most common studied problems in recent years, however, this classic optimization problem has to achieve two conflicting objectives, i.e. minimizing the total tardiness and minimizing the total wastes, if the scheduling is done in the context of plastic injection industry where jobs are splitting and molds are important constraints. This paper proposes a mathematical model for scheduling parallel machines with splitting jobs and resource constraints. Two minimization objectives - the total tardiness and the number of waste - are considered, simultaneously. The obtained model is a bi-objective integer linear programming model that is shown to be of NP-hard class optimization problems. In this paper, a novel Multi-Objective Volleyball Premier League (MOVPL) algorithm is presented for solving the aforementioned problem. This algorithm uses the crowding distance concept used in NSGA-II as an extension of the Volleyball Premier League (VPL) that w...

One of the most important functions of manufacturers and producers related to supply chain issues... more One of the most important functions of manufacturers and producers related to supply chain issues and decisions is management of supply chain orders. But in this way, there are several questions such as (a) what is the best order portfolio between received orders? (b) what are various decision scenarios under uncertainty? Indeed, these are the questions we want to answer in this paper. The purpose of this research is designing the mathematical model of supply chain orders management belongs to an Automakers Company. For this reason, we use both robust optimization and activity based costing method to gain more accurate and better solutions. Due to cost structure used in this model and complexity of cost objects as well as uncertainty of some parameters, we change this model to a robust model to obtain more reliable results. Finally, to assess the validity of the model and quality of solutions, we use simulation techniques. Findings show the model is valid and applicable to determine...

Medical & Biological Engineering & Computing, 2022

Medical oxygen is a critical element in the treatment process of COVID-19 patients which its shor... more Medical oxygen is a critical element in the treatment process of COVID-19 patients which its shortage impacts the treatment process adversely. This study aims to apply machine learning (ML) to predict the requirement for oxygen-based treatment for hospitalized COVID-19 patients. In the first phase, demographic information, symptoms, and patient's background were extracted from the databases of two local hospitals in Iran, and preprocessing actions were applied. In the second step, the related features were selected. Lastly, five ML models including logistic regression (LR), random forest (RF), XGBoost, C5.0, and neural networks (NNs) were implemented and compared based on their accuracy and capability. Among the variables related to the patient's background, consuming opium due to the high rate of opium users in Iran was considered in the models. Of the 398 patients included in the study, 112 (28.14%) received oxygen-based treatment. Shortness of breath (71.42%), fever (62.5%), and cough (59.82%) had the highest frequency in patients with oxygen requirements. The most important variables for prediction were shortness of breath, cough, age, and fever. For opioid-addicted patients, in addition to the high mortality rate (23.07%), the rate of oxygen-based treatment was twice as high as non-addicted patients. XGBoost and LR obtained the highest area under the curve with values of 88.7% and 88.3%, respectively. For accuracy, LR and NNs achieved the best and same accuracy (86.42%). This approach provides a tool that accurately predicts the need for oxygen in the treatment process of COVID-19 patients and helps hospital resource management.

Nonlinear Dynamics, 2022

The COVID-19 pandemic shows to have a huge impact on people's health and countries' infrastructur... more The COVID-19 pandemic shows to have a huge impact on people's health and countries' infrastructures around the globe. Iran was one of the first countries that experienced the vast prevalence of the coronavirus outbreak. The Iranian authorities applied various non-pharmaceutical interventions to eradicate the epidemic in different periods. This study aims to investigate the effectiveness of non-pharmaceutical interventions in managing the current Coronavirus pandemic and to predict the next wave of infection in Iran. To achieve the research objective, the number of cases and deaths before and after the interventions was studied and the effective reproduction number of the infection was analyzed under various scenarios. The SEIR generic model was applied to capture the dynamic of the pandemic in Iran. To capture the effects of different interventions, the corresponding reproduction number was considered. Depending on how people are responsive to interventions, the effectiveness of each intervention has been investigated. Results show that the maximum number of the total of infected individuals will occur around the end of May and the start of June 2021. It is concluded that the outbreak could be smoothed if full lockdown and strict quarantine continue. The proposed modeling could be used as an assessment tool to evaluate the effects of different interventions in new outbreaks.

2019 International Conference on Automation, Computational and Technology Management (ICACTM), 2019

Time and resource management are two crucial activities within the project management framework. ... more Time and resource management are two crucial activities within the project management framework. This paper demonstrates how resource assignment Petri net (RAPN) a class of colored Petri nets, is applied effectively for modeling and scheduling of construction projects, known as a resource- constrained project scheduling (RCPSP). It captures the dynamic behavior of the project at runtime and enables the decision maker to investigate interactions between resources and project requirements. To determine the most suitable scheduling of project resources, the dynamic population and steady-state ge- netic algorithm (DP–SS GA) is integrated into the modeling framework. It is used to identify the best scheduling plan for different working schemes. In order to illustrate different resource assignment strategies and capture the dynamic inter- actions between resources and activities, a running case study is used. It is found that the modeling framework is capable of capturing the model requirements of a construction project. Compared to the exact solution generated by classic project management tools, the proposed model produced a near optimal solution.

Iranian banking sector is under tremendous pressure to re-engineer its processes to meet requirem... more Iranian banking sector is under tremendous pressure to re-engineer its processes to meet requirements of eBanking services. Business process re-engineering practices have a great failure rate around the world. In order to better understand key elements in implementation of BPR projects, interpretive structural modeling approach have been applied. This paper proposes the underlying theoretical framework to identify critical success factors of BPR projects in banking sector.

The multiple traveling salesman problem (mTSP) is a NP-hard combinatorial optimization problem. I... more The multiple traveling salesman problem (mTSP) is a NP-hard combinatorial optimization problem. It has many real-world applications, for example, the School Bus Routing Problem, and the Pickup and Delivery Problem. In the mTSP, a set of routes is assigned to m salesmen who all start from and return to a home city(depot). In this problem, each other node is located in exactly one tour, the number of nodes visited by a salesman lies within a predetermined interval, and the overall cost of visiting all nodes is minimized. In this study, we discuss how to use constraint programming (CP) to formulate and solve mTSP by applying interval variables, global constraints and domain filtering algorithms. We propose a CP model for the mTSP. The CPmTSP was tested on a set of benchmark instances from the TSPLIB. Solutions of the CPmTSP are compared to the ILP-CPLEX of mTSP model and other algorithms (ACO, SW+ASelite, GELS-GA and Enhanced GA) in the literature. The computational results indicate th...

Objective: The aim of the research was investigating and visualizing the intellectual structure o... more Objective: The aim of the research was investigating and visualizing the intellectual structure of thermodynamics subject area based on outputs of Iranian scholars of the field indexed in Thomson Reuters Web of Science during time span of 1990-2009. Method: The population of the research was all references of the mentioned publications. The sample was the top 1 percent cited scholars of the field. This scientometric research is based on citation analysis and the author-cocitation analysis and social network analysis have been utilized for evaluating the base authors in citation network of the field. Findings: The result of the research is presenting a macro image of the intellectual foundations of the field and its analysis. Also, we analyzed and ranked the subject area based on its specialties, and new social network, temporal and citation indicators such as novelty, centrality, modularity, silhouette, density.

With increasing demand for medical services, emergency departments (ED) are facing problems such ... more With increasing demand for medical services, emergency departments (ED) are facing problems such as overcrowding and dissatisfaction. Improving the key performance indicators of EDs has been the focal point of healthcare management. This paper addresses performance analysis of ED of a general hospital. To this aim, a discrete event dynamic modeling approach is used to model the ED processes. The model employs a hierarchical timed Coloured Petri net framework in a concise and detailed way to capture patient flow and care processes within the ED. The simulation model was validated against historical data and then different types of scenarios were used to assess, compare and improve ED key performance indicators, such as patients waiting time, length of stay (LOS), and resource utilization rate. The proposed model helped the hospital policy makers to configure the ED in a way to improve its efficiency and staff satisfaction.

In this paper, the pricing of a European call option on the underlying asset is performed by usin... more In this paper, the pricing of a European call option on the underlying asset is performed by using a Monte Carlo method, one of the powerful simulation methods, where the price development of the asset is simulated and value of the claim is computed in terms of an expected value. The proposed approach, applied in Monte Carlo simulation, is based on the Black-Scholes equation which generally defined the pricing of European call options in a dynamic environment. Therefore, the main goal of this study is how can Monte Carlo be applied to finance? Although it is stated that because of being based on randomness, the Monte Carlo method has its obvious disadvantages and does not yield solutions for all possible stock prices, by applying Black-Scholes formula, it is efficient to use this method for calculating payoff. Hence, in the matter of this paper, we introduce the Black-Scholes model and Monte Carlo simulations as main tools to determine.

Operations Research for Health Care, 2021

Journal of Cleaner Production, 2021

Recent decades have seen increasing utilization of optimization packages, based on Operations Res... more Recent decades have seen increasing utilization of optimization packages, based on Operations Research 4 and Mathematical Programming techniques, for effective management of the provision of goods and services in distribution systems. Large numbers of real-world applications, both in North America and Europe, have widely shown that the use of computerized procedures for distribution process planning produces substantial savings (generally from 5% to 20%) in global transportation costs. It is easy to see that the impact of these savings on the global economic system is significant. The transportation process involves all stages of production and distribution systems and represents a relevant component (generally 10 from 10% to 20%) of the final cost of goods. The green vehicle routing problem (GVRP) is an emerging research field that attracts many researchers. This survey paper aims to classify and review the literature on GVRPs from various perspectives. This paper covers publications between 2006 and 2019 including 309 13 papers. To this end, a systematic literature review has been implemented in order to respond to corresponding questions related to this area and proposed an extensive structure compromising various aspects including variants of GVRPs, objective functions, uncertainty, and solutions approach to analyze GVRPs studies in different perspectives. Some new research areas have been drawn based on problem classification, uncertainties, solution methodologies, and finally, the objective function approaches for 18 future research directions and the results of this study show that researches on GVRPs are relatively fresh 19 and there is still a room for large improvements in several areas. 20

Applied Soft Computing, 2021

Abstract This paper proposes a modified marine predators algorithm based on quantum theory to han... more Abstract This paper proposes a modified marine predators algorithm based on quantum theory to handle the multilevel image segmentation problem. The main aims of using quantum theory is to enhance the ability of marine predators algorithm to find the optimal threshold levels to enhance the segmentation process. The proposed quantum marine predators algorithm gets the idea of finding a particle in the space based on a possible function borrowed from the Schrodinger wave function that determines the position of each particle at any time. This rectification in the search mechanism of the marine predators algorithm contributes to strengthening of exploration and exploitation of the algorithm. To analyze the performance of the proposed algorithm, we conduct a set of experiments. In the first experiment, the results of the developed quantum marine predators algorithm are compared with eight well-known meta-heuristics based on benchmark test functions. The second experiment demonstrates the applicability of the algorithm, in addressing multilevel threshold image segmentation. A set of ten gray-scale images assess the quality of the quantum marine predators algorithm and its performance is compared with other meta-heuristic algorithms. The experimental results show that the proposed algorithm performs well compared with other algorithms in terms of convergence and the quality of segmentation.

Operational Research, 2020

Over the past decades, the Multicommodity Network Flow (MCNF) problem has grown popular in the ac... more Over the past decades, the Multicommodity Network Flow (MCNF) problem has grown popular in the academic literature and a growing number of researchers are interested in this field. It is a powerful operational research approach to tackle and solve many complicated problems, especially in transportation and telecommunication contexts. Yet, few literature reviews have made an effort to classify the existing articles accordingly. In this article, we present a taxonomic review of the MCNF literature published between 2000 and 2019. Based on an adapted version of an existing comprehensive taxonomy, we have classified 263 articles into two main categories of applications and solution methods. We have also analyzed the research interests in the MCNF literature. This classification is the first to categorize the articles into this level of detail. Results show that there are topics, which need to be addressed in future researches.

Knowledge-Based Systems, 2020

Thi s is a n O p e n Acc e s s d o c u m e n t d o w nlo a d e d fro m ORCA, C a r diff U niv e r... more Thi s is a n O p e n Acc e s s d o c u m e n t d o w nlo a d e d fro m ORCA, C a r diff U niv e r si ty' s in s tit u tio n al r e p o si to ry: h t t p s://o r c a. c a r diff.a c. u k/ 1 3 0 5 4 1/ This is t h e a u t h o r's v e r sio n of a w o r k t h a t w a s s u b mi t t e d t o / a c c e p t e d fo r p u blic a tio n. Cit a tio n fo r fin al p u blis h e d ve r sio n: M o g h d a ni, R ez a, S ali mif a r d, Kho d a k a r a m , D e mir, E m r a h a n d B e ny e t t o u, Abd elk a d e r 2 0 2 0. M ul ti-o bj e c tiv e volley b all p r e m i e r le a g u e al g o ri t h m. Kno wl e d g e-B a s e d S y s t e m s