International Journal of Operational Research Impact Factor & Information

Publisher: Inderscience

Journal description

IJOR is a fully refereed journal generally covering new theory and application of operations research (OR) techniques and models that include inventory, queuing, transportation, game theory, scheduling, project management, mathematical programming, decision-support systems, multi-criteria decision making, artificial intelligence, neural network, fuzzy logic, expert systems, and simulation. New theories and applications of operations research models are welcome to IJOR. Modelling and optimisation have become an essential function of researchers and practitioners in a networked global economy. New theory development in operations research and their applications in new economy and society have been limited. In the information intensive society and economy, decisions are made based on the analysis of data available. Operations research techniques and models need to be integrated with computers for the purpose of analysis, optimisation and application in decision making. This development has led the researchers and practitioners to look for new operational research models and their applications in global economy and society. For this purpose, the modelling and optimisation have become a paramount important. IJOR will act as a platform to encourage further research in OR and MS theory and applications. Globalisation of market and operations places a tremendous pressure in making timely and accurate decisions using the analysis of data and more accurate information. This signifies the importance of developing suitable operations research techniques and models and their applications are a paramount important in the 21st century global society and economy.

Current impact factor: 0.00

Impact Factor Rankings

Additional details

5-year impact 0.00
Cited half-life 0.00
Immediacy index 0.00
Eigenfactor 0.00
Article influence 0.00
Website International Journal of Operational Research website
Other titles International journal of operational research (Online), IJOR, Operational research
ISSN 1745-7653
OCLC 67616113
Material type Document, Periodical, Internet resource
Document type Internet Resource, Computer File, Journal / Magazine / Newspaper

Publisher details

Inderscience

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author cannot archive a post-print version
  • Restrictions
    • 6 months embargo
  • Conditions
    • Cannot archive until publication
    • Author's pre-print and Author's post-print on author's personal website, institutional repository or subject repository
    • Publisher copyright and source must be acknowledged
    • Must link to journal webpage and /or DOI
    • Publisher's version/PDF cannot be used, unless covered by funding agency rules
    • Authors covered by funding agency rules, may post the Publisher's Version/PDF in subject repositories after a 6 months embargo
    • Reviewed 10/02/2014
    • Author's post-print equates to Inderscience's Proof
  • Classification
    ​ yellow

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: Uncertainty plays an important role in predicting the future earning of the assets in the financial market and it is generally measured in terms of probability. But in some cases, it would be a good idea for an investor to state the expected returns on assets in the form of closed intervals. Therefore, in this paper, we consider a portfolio selection problem wherein expected return of any asset, risk level and proportion of total investment on assets are in the form of interval, and obtain an optimum (best) portfolio. Such portfolio gives the total expected return and proportion of total investment on assets in the form of interval. The proposed portfolio model is solved by considering an equivalent linear programming problem, where all the parameters of the objective function and constraints as well as decision variables are expressed in form of intervals. The procedure gives a strongly feasible optimal interval solution of such problem based on partial order relation between intervals. Efficacy of the results is demonstrated by means of numerical examples.
    International Journal of Operational Research 07/2015;
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    ABSTRACT: Four multiresponse optimization problems were simulated under the RSM framework to describe real-life situations and provide a fair basis to compare the performance of optimization criteria built on different approaches. Different response types, feasible regions, number of responses and variables as well as adverse variance conditions were considered in each problem. Performance metrics usefulness to take more informed decisions about solution selection is also illustrated. An unusual graphical representation of the results provides useful information about working abilities and performance of tested criteria.
    International Journal of Operational Research 03/2015; 23(1):15. DOI:10.1504/IJOR.2015.068742
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    ABSTRACT: In the present investigation, a multi channel infinite buffer queue under N-policy has been analyzed using matrix geometric method. The analytical results are further computed for the purpose of validation by one of the fastest growing soft computing technique i.e. artificial neural network (ANN). The proposed model can be successfully applicable in a real-time wireless communication network by developing neural network controller. The wireless system consists of multi channels and a separate queue in front of each one of them. The concept of N-policy is taken into consideration according to which the server initiates the service only when N jobs are accumulated in the system. The arriving pattern of the traffic (voice/data packets) to the queues in front of different channels follows the Poisson distribution whereas the service times are exponentially distributed. Matrix geometric method is employed to obtain the queue size distribution at equilibrium. Various performance indices such as blocking probabilities, throughput, average delay etc. are obtained. The usefulness of the proposed approach is illustrated by taking a specific example. The numerical procedure to compute various state probabilities and other performance indices is outlined. The sensitivity analysis has also been carried out to facilitate the insights of the controllable parameters for the improvement of real-time system. Keywords: N-policy; Multi-channel queue; Queue length; Blocking; Matrix geometric; Artificial neural network.
    International Journal of Operational Research 01/2015;
  • International Journal of Operational Research 01/2015; 22(2):167-193.
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    ABSTRACT: Nowadays, defining new projects is significantly vital and necessary for many organizations and companies. The problem arise here is how to select an appropriate portfolio from a set of candidate projects. A good combination of projects can extensively promote the organizations in their competitive performance. Thus, the purpose of this study is to present a practical model in addition to some solution approaches to choose the best and proper project portfolios with the considerations of projects’ interactions, quantitative and qualitative criteria, and practical constraints. A linear formulation has been proposed which considers the interaction effects and integrates the number of selected projects, the segmentations, and the budgetary constraints into a single set of constraints. In order to solve the proposed model, a genetic algorithm and also a differential evolution algorithm are presented. Moreover, the efficiencies of these two algorithms are compared with an exact method using various numerical examples. Finally, through a case study the performance of the model is demonstrated.
    International Journal of Operational Research 12/2014; In press.
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    ABSTRACT: in this paper, we propose an integrated methodology of Fault-tree analysis (FTA) and the fuzzy analytical hierarchy process (AHP) approach, which provide means to integrate the qualitative and quantitative information to the group decision-making process for analyzing green supply chain risks under the fuzzy surroundings. In the proposed methodology, initially, a fault tree diagram is constructed, which includes the probable criteria, and sub-criteria of the green supply chain risks, and later, using the fuzzy AHP approach, these criteria and sub-criteria were prioritized for risk assessment. A total eight risk criteria and thirty sub-criteria were identified based on relevant literature and the experts input. The research findings illustrates that the product recovery risks and process risks criteria possess highest priority and need considerable managerial responsiveness for reducing the green supply chain susceptibility and hence performance improvement. Further, a plastic manufacturer green supply chain case illustrative example is presented to show the real-world applicability of the study. The managerial implications and conclusions are also discussed in the end.
    International Journal of Operational Research 04/2014;
  • International Journal of Operational Research 03/2014;
  • International Journal of Operational Research 03/2014;
  • International Journal of Operational Research 01/2014; 19(2):32-42.
  • International Journal of Operational Research 01/2014;
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    ABSTRACT: In addition to the system’s complexity and uncertainty, healthcare managers face many challenges, including the increasing levels of demand and patient expectations at the time of more budget constraints enforced on healthcare service in Ireland. The delivery of a better patient care requires effective decision making especially in planning of healthcare resources. For an emergency department (ED) of a leading university hospital in the south of Dublin City, a decision support application for resource planning considering multiple performance indicators was developed. A comprehensive discrete event simulation model was used to identify the most significant variables and key factors that affect the ED performance. Combining this model with Taguchi orthogonal arrays and data envelopment analysis in an integrated manner helps to improve decision-making procedure in terms of systematic scenarios’ selection and evaluation. The developed system is used for resource planning and also to assess risks due to the shortage of medical staff of the emergency department. Results show the importance of balancing doctor numbers employed within ED in order to maintain reasonable patient throughput time.
    International Journal of Operational Research 01/2014; 19(1):40. DOI:10.1504/IJOR.2014.057843