|
15 | 15 | "\n", |
16 | 16 | ">This notebook is part of **[Prescriptive Analytics for Python](http://ibmdecisionoptimization.github.io/docplex-doc/)**\n", |
17 | 17 | ">\n", |
18 | | - ">It requires either an [installation of CPLEX Optimizers](http://ibmdecisionoptimization.github.io/docplex-doc/getting_started.html) or it can be run on [IBM Watson Studio Cloud](https://www.ibm.com/cloud/watson-studio/>) (Sign up for a [free IBM Cloud account](https://dataplatform.cloud.ibm.com/registration/stepone?context=wdp&apps=all>)\n", |
19 | | - "and you can start using Watson Studio Cloud right away).\n", |
| 18 | + ">It requires either an [installation of CPLEX Optimizers](http://ibmdecisionoptimization.github.io/docplex-doc/getting_started.html) or it can be run on [IBM Cloud Pak for Data as a Service](https://www.ibm.com/products/cloud-pak-for-data/as-a-service/) (Sign up for a [free IBM Cloud account](https://dataplatform.cloud.ibm.com/registration/stepone?context=wdp&apps=all>)\n", |
| 19 | + "and you can start using `IBM Cloud Pak for Data as a Service` right away).\n", |
| 20 | + ">\n", |
| 21 | + "> CPLEX is available on <i>IBM Cloud Pack for Data</i> and <i>IBM Cloud Pak for Data as a Service</i>:\n", |
| 22 | + "> - <i>IBM Cloud Pak for Data as a Service</i>: Depends on the runtime used:\n", |
| 23 | + "> - <i>Python 3.x</i> runtime: Community edition\n", |
| 24 | + "> - <i>Python 3.x + DO</i> runtime: full edition\n", |
| 25 | + "> - <i>Cloud Pack for Data</i>: Community edition is installed by default. Please install `DO` addon in `Watson Studio Premium` for the full edition\n", |
20 | 26 | "\n", |
21 | 27 | "To follow the examples in this section, some knowledge about optimization (math programming or constraint programming) and about modeling optimization problems is necessary.\n", |
22 | 28 | "For beginners in optimization, following the online free Decision Optimization tutorials ([here](https://ibmdecisionoptimization.github.io/tutorials/html/Linear_Programming.html) and [here](https://ibmdecisionoptimization.github.io/tutorials/html/Beyond_Linear_Programming.html)) might help to get a better understanding of Mathematical Optimization.\n", |
|
3320 | 3326 | "source": [ |
3321 | 3327 | "## References\n", |
3322 | 3328 | "* [CPLEX Modeling for Python documentation](https://rawgit.com/IBMDecisionOptimization/docplex-doc/master/docs/index.html)\n", |
3323 | | - "* [Decision Optimization on Cloud](https://developer.ibm.com/docloud/)\n", |
| 3329 | + "* [IBM Decision Optimization](https://www.ibm.com/analytics/decision-optimization)\n", |
3324 | 3330 | "* Need help with DOcplex or to report a bug? Please go [here](https://stackoverflow.com/questions/tagged/docplex).\n", |
3325 | 3331 | "* Contact us at dofeedback@wwpdl.vnet.ibm.com." |
3326 | 3332 | ] |
|
3329 | 3335 | "cell_type": "markdown", |
3330 | 3336 | "metadata": {}, |
3331 | 3337 | "source": [ |
3332 | | - "Copyright © 2017, 2018 IBM. IPLA licensed Sample Materials." |
| 3338 | + "Copyright © 2017, 2021 IBM. IPLA licensed Sample Materials." |
3333 | 3339 | ] |
| 3340 | + }, |
| 3341 | + { |
| 3342 | + "cell_type": "code", |
| 3343 | + "execution_count": null, |
| 3344 | + "metadata": {}, |
| 3345 | + "outputs": [], |
| 3346 | + "source": [] |
3334 | 3347 | } |
3335 | 3348 | ], |
3336 | 3349 | "metadata": { |
3337 | 3350 | "anaconda-cloud": {}, |
3338 | 3351 | "kernelspec": { |
3339 | | - "display_name": "Python 2", |
| 3352 | + "display_name": "Python 3", |
3340 | 3353 | "language": "python", |
3341 | | - "name": "python2" |
| 3354 | + "name": "python3" |
3342 | 3355 | }, |
3343 | 3356 | "language_info": { |
3344 | 3357 | "codemirror_mode": { |
3345 | 3358 | "name": "ipython", |
3346 | | - "version": 2 |
| 3359 | + "version": 3 |
3347 | 3360 | }, |
3348 | 3361 | "file_extension": ".py", |
3349 | 3362 | "mimetype": "text/x-python", |
3350 | 3363 | "name": "python", |
3351 | 3364 | "nbconvert_exporter": "python", |
3352 | | - "pygments_lexer": "ipython2", |
3353 | | - "version": "2.7.15" |
| 3365 | + "pygments_lexer": "ipython3", |
| 3366 | + "version": "3.7.8" |
3354 | 3367 | } |
3355 | 3368 | }, |
3356 | 3369 | "nbformat": 4, |
|
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