Example of Computational Management Science format
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Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format
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Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format Example of Computational Management Science format
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open access Open Access

Computational Management Science — Template for authors

Publisher: Springer
Categories Rank Trend in last 3 yrs
Management Information Systems #57 of 114 down down by 24 ranks
Information Systems #206 of 329 down down by 63 ranks
journal-quality-icon Journal quality:
Good
calendar-icon Last 4 years overview: 108 Published Papers | 189 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 14/06/2020
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Related Journals

open access Open Access

Springer

Quality:  
High
CiteRatio: 3.3
SJR: 0.48
SNIP: 1.716
open access Open Access
recommended Recommended

Springer

Quality:  
High
CiteRatio: 7.7
SJR: 1.426
SNIP: 1.845
open access Open Access
recommended Recommended

Elsevier

Quality:  
High
CiteRatio: 8.6
SJR: 0.565
SNIP: 1.611

Journal Performance & Insights

CiteRatio

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

A measure of average citations received per peer-reviewed paper published in the journal.

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

1.8

28% from 2019

CiteRatio for Computational Management Science from 2016 - 2020
Year Value
2020 1.8
2019 2.5
2018 2.3
2017 2.1
2016 1.9
graph view Graph view
table view Table view

0.683

24% from 2019

SJR for Computational Management Science from 2016 - 2020
Year Value
2020 0.683
2019 0.902
2018 0.867
2017 0.595
2016 0.424
graph view Graph view
table view Table view

0.888

8% from 2019

SNIP for Computational Management Science from 2016 - 2020
Year Value
2020 0.888
2019 0.966
2018 0.99
2017 1.066
2016 1.055
graph view Graph view
table view Table view

insights Insights

  • CiteRatio of this journal has decreased by 28% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

insights Insights

  • SJR of this journal has decreased by 24% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has decreased by 8% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

Computational Management Science

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Springer

Computational Management Science

Computational Management Science is an international journal focusing on all computational aspects of management science. These include theoretical and empirical analysis of computational models; computational statistics; analysis and applications of constrained, unconstrained...... Read More

Management Information Systems

Business, Management and Accounting

i
Last updated on
13 Jun 2020
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ISSN
1619-697X
i
Impact Factor
Medium - 0.775
i
Open Access
No
i
Sherpa RoMEO Archiving Policy
Green faq
i
Plagiarism Check
Available via Turnitin
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Endnote Style
Download Available
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Bibliography Name
SPBASIC
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Citation Type
Author Year
(Blonder et al, 1982)
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Bibliography Example
Beenakker CWJ (2006) Specular andreev reflection in graphene. Phys Rev Lett 97(6):067,007, URL 10.1103/PhysRevLett.97.067007

Top papers written in this journal

Journal Article DOI: 10.1007/S10287-004-0020-Y
Partitioning procedures for solving mixed-variables programming problems
J. F. Benders1

Abstract:

Paper presented to the 8th International Meeting of the Institute of Management Sciences, Brussels, August 23-26, 1961.
1,750 Citations
Journal Article DOI: 10.1007/S10287-007-0046-Z
ETSAP-TIAM: the TIMES integrated assessment model Part I: Model structure
Richard Loulou1, Maryse Labriet

Abstract:

In this first part of a two-part article, the principal characteristics of the TIMES model and of its global incarnation as ETSAP-TIAM are presented and discussed. TIMES was conceived as a descendent of the MARKAL and EFOM paradigms, to which several new features were added to extend its functionalities and its applicability ... In this first part of a two-part article, the principal characteristics of the TIMES model and of its global incarnation as ETSAP-TIAM are presented and discussed. TIMES was conceived as a descendent of the MARKAL and EFOM paradigms, to which several new features were added to extend its functionalities and its applicability to the exploration of energy systems and the analysis of energy and environmental policies. The article stresses the technological nature of the model and its economic foundation and properties. The article stays at the conceptual and practical level, while a companion article is devoted to the more detailed formulation of TIMES equations. Special sections are devoted to the description of four optional features of TIMES: lumpy investments, endogenous technology learning, stochastic programming, and the climate module. The article ends with a brief description of recent applications of the ETSAP-TIAM model. read more read less
View PDF
502 Citations
open accessOpen access Journal Article DOI: 10.1007/S10287-009-0093-8
Quasi-variational inequalities, generalized Nash equilibria, and multi-leader-follower games
Jong-Shi Pang1, Masao Fukushima2

Abstract:

In Pang and Fukushima (Comput Manage Sci 2:21–56, 2005), a sequential penalty approach was presented for a quasi-variational inequality (QVI) with particular application to the generalized Nash game. To test the computational performance of the penalty method, numerical results were reported with an example from a multi-leade... In Pang and Fukushima (Comput Manage Sci 2:21–56, 2005), a sequential penalty approach was presented for a quasi-variational inequality (QVI) with particular application to the generalized Nash game. To test the computational performance of the penalty method, numerical results were reported with an example from a multi-leader-follower game in an electric power market. However, due to an inverted sign in the penalty term in the example and some missing terms in the derivatives of the firms’ Lagrangian functions, the reported numerical results in Pang and Fukushima (Comput Manage Sci 2:21–56, 2005) are incorrect. Since the numerical examples of this kind are scarce in the literature and this particular example may be useful in the future research, we report the corrected results. read more read less

Topics:

Penalty method (58%)58% related to the paper, Best response (58%)58% related to the paper, Epsilon-equilibrium (56%)56% related to the paper, Nash equilibrium (55%)55% related to the paper, Equilibrium selection (53%)53% related to the paper
View PDF
424 Citations
open accessOpen access Journal Article DOI: 10.1007/S10287-010-0125-4
Progressive hedging innovations for a class of stochastic mixed-integer resource allocation problems
Jean-Paul Watson1, David L. Woodruff2

Abstract:

Numerous planning problems can be formulated as multi-stage stochastic programs and many possess key discrete (integer) decision variables in one or more of the stages. Progressive hedging (PH) is a scenario-based decomposition technique that can be leveraged to solve such problems. Originally devised for problems possessing ... Numerous planning problems can be formulated as multi-stage stochastic programs and many possess key discrete (integer) decision variables in one or more of the stages. Progressive hedging (PH) is a scenario-based decomposition technique that can be leveraged to solve such problems. Originally devised for problems possessing only continuous variables, PH has been successfully applied as a heuristic to solve multi-stage stochastic programs with integer variables. However, a variety of critical issues arise in practice when implementing PH for the discrete case, especially in the context of very difficult or large-scale mixed-integer problems. Failure to address these issues properly results in either non-convergence of the heuristic or unacceptably long run-times. We investigate these issues and describe algorithmic innovations in the context of a broad class of scenario-based resource allocation problem in which decision variables represent resources available at a cost and constraints enforce the need for sufficient combinations of resources. The necessity and efficacy of our techniques is empirically assessed on a two-stage stochastic network flow problem with integer variables in both stages. read more read less

Topics:

Stochastic optimization (59%)59% related to the paper, Resource allocation (55%)55% related to the paper, Heuristic (52%)52% related to the paper, Integer (computer science) (51%)51% related to the paper, Flow network (50%)50% related to the paper
View PDF
300 Citations
Journal Article DOI: 10.1007/S10287-007-0045-0
ETSAP-TIAM: the TIMES integrated assessment model. part II: mathematical formulation
Richard Loulou1

Abstract:

This article is a companion to “ETSAP-TIAM: the TIMES integrated assessment model. part I: model structure”. It contains three sections, presenting respectively: the simplified formulation of the TIMES Linear Program (Sect. 1), the details of the computation of the supply demand equilibrium (Sect. 2), and the Endogenous Techn... This article is a companion to “ETSAP-TIAM: the TIMES integrated assessment model. part I: model structure”. It contains three sections, presenting respectively: the simplified formulation of the TIMES Linear Program (Sect. 1), the details of the computation of the supply demand equilibrium (Sect. 2), and the Endogenous Technology Learning Formulation (Sect. 3). The full details of these three formulations are available in the complete TIMES documentation at www.etsap/org/documentation. read more read less
197 Citations
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Computational Management Science format uses SPBASIC citation style.

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Frequently asked questions

1. Can I write Computational Management Science in LaTeX?

Absolutely not! Our tool has been designed to help you focus on writing. You can write your entire paper as per the Computational Management Science guidelines and auto format it.

2. Do you follow the Computational Management Science guidelines?

Yes, the template is compliant with the Computational Management Science guidelines. Our experts at SciSpace ensure that. If there are any changes to the journal's guidelines, we'll change our algorithm accordingly.

3. Can I cite my article in multiple styles in Computational Management Science?

Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the Computational Management Science citation style.

4. Can I use the Computational Management Science templates for free?

Sign up for our free trial, and you'll be able to use all our features for seven days. You'll see how helpful they are and how inexpensive they are compared to other options, Especially for Computational Management Science.

5. Can I use a manuscript in Computational Management Science that I have written in MS Word?

Yes. You can choose the right template, copy-paste the contents from the word document, and click on auto-format. Once you're done, you'll have a publish-ready paper Computational Management Science that you can download at the end.

6. How long does it usually take you to format my papers in Computational Management Science?

It only takes a matter of seconds to edit your manuscript. Besides that, our intuitive editor saves you from writing and formatting it in Computational Management Science.

7. Where can I find the template for the Computational Management Science?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Computational Management Science's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

8. Can I reformat my paper to fit the Computational Management Science's guidelines?

Of course! You can do this using our intuitive editor. It's very easy. If you need help, our support team is always ready to assist you.

9. Computational Management Science an online tool or is there a desktop version?

SciSpace's Computational Management Science is currently available as an online tool. We're developing a desktop version, too. You can request (or upvote) any features that you think would be helpful for you and other researchers in the "feature request" section of your account once you've signed up with us.

10. I cannot find my template in your gallery. Can you create it for me like Computational Management Science?

Sure. You can request any template and we'll have it setup within a few days. You can find the request box in Journal Gallery on the right side bar under the heading, "Couldn't find the format you were looking for like Computational Management Science?”

11. What is the output that I would get after using Computational Management Science?

After writing your paper autoformatting in Computational Management Science, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is Computational Management Science's impact factor high enough that I should try publishing my article there?

To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for Computational Management Science?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for Computational Management Science. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In Computational Management Science?

The 5 most common citation types in order of usage for Computational Management Science are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

15. How do I submit my article to the Computational Management Science?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Computational Management Science's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download Computational Management Science in Endnote format?

Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in Computational Management Science Endnote style according to Elsevier guidelines.

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I spent hours with MS word for reformatting. It was frustrating - plain and simple. With SciSpace, I can draft my manuscripts and once it is finished I can just submit. In case, I have to submit to another journal it is really just a button click instead of an afternoon of reformatting.

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