International Journal of Operational Research (Int J Oper Res)
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
|Website||International Journal of Operational Research website|
|Other titles||International journal of operational research (Online), IJOR, Operational research|
|Material type||Document, Periodical, Internet resource|
|Document type||Internet Resource, Computer File, Journal / Magazine / Newspaper|
- Author can archive a pre-print version
- Author cannot archive a post-print version
- 6 months embargo
- 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
Publications in this journal
Article: ANALYSIS OF A NON MARKOVIAN SINGLE SERVER BATCH ARRIVAL QUEUEING SYSTEM OF COMPULSORY THREE STAGES OF SERVICES WITH FOURTH OPTIONAL STAGE SERVICE, SERVICE INTERRUPTIONS AND DETERMINISTIC SERVER VACATIONS it is forthcoming at: http://www.inderscience.com/info/ingeneral/forthcoming.php?jcode=ijor[Show abstract] [Hide abstract] ABSTRACT: Abstract: This paper deals with the steady state analysis of a single server batch arrival queueing system with three stages of compulsory service. An added assumption of fourth stage optional service is considered. After service completion the server may take a vacation. In this model, the vacation is of fixed duration. Busy server may break down at any instant. It is followed by a repair process. Service time, vacation time and repair time follows general distribution. The steady state probability generating function for the system is obtained by using supplementary variable method. System performance measures are also determined. Some special cases of the model are also discussed. Model is justified by means of numerical illustration.
- [Show abstract] [Hide abstract] ABSTRACT: We study a single server queue with Poisson arrivals, two optional services following a general service time distributions. The first service is essential. Other two services are optional. Only some of the arriving customers demand the first optional service or the second optional service. We derive the system size distribution at random points and at departure points and other performance indices such as average number of customers and the average waiting time in the queue and the system by employing generating function and supplementary variable techniques. By taking numerical illustration, the sensitivity analysis is also conducted to determine the effects of the system parameters on various performance measures of system state are derived.
- [Show abstract] [Hide abstract] ABSTRACT: To maximise rough turning efficiency, using robust constant parameters or constant measured parameter adaptive control is not enough, but true adaptive control is needed. In order to safely optimise volume removal rate, it is necessary to model the cutting instability appearing at high levels of feed rate. This allows the prediction of the phenomenon and thus use of maximal cutting values while maintaining safe and controlled operation at all times by applying adaptive control. In this paper, various models are studied based on cutting parameters, sensor data and a combination of both. The capabilities of the models to classify cutting samples captured from the machining process are then examined and a model suitable for cutting condition prediction is recommended.
- [Show abstract] [Hide abstract] ABSTRACT: In this paper, a simple and novel procedure is proposed to determine a set of buy-back prices and the wholesale costs to maximize the profit of a two-stage supply chain consisting of one supplier and one retailer. A supplier (or manufacturer) can implement a buy-back policy to influence the quantity ordered by its retailer. We have developed a simple rule to achieve channel coordination in a two-stage supply chain dealing with a limited life product. A numerical experiment has been conducted to illustrate the proposed model. Sensitivity analyses are performed to show the impact of various parameters on supply chain profit. The results depict that a higher degree of channel coordination not only increases the expected supply chain profit but also decreases the impact of demand uncertainty on expected profit. Moreover, the sensitivity results show that the increase in the degree of channel coordination decreases the coefficient of variation in retailers profit. Finally, the implications of using these results for the managers have been discussed.
- [Show abstract] [Hide abstract] ABSTRACT: The design of RMS initiates with the classification of parts into families, after which reconfiguration of the system is carried out to cater new part families. It is important that parts must be grouped into logical families based on similarities either in manufacturing or design attributes. Generally, production system maintains a large database of existing part families, and once any new part comes in, the efforts must be focused on deciding upon an appropriate existing part family in which the new part may be grouped with. In literature, most of the approaches are based on part family formation from beginning with no consideration of how the existing part family database can be utilised to decide upon a suitable existing part family for a new part. This paper proposed a neural network classification-based approach for such classification. The developed methodology is explained with the help of a numerical illustration.
- [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.
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