Tag search results. IBM ILOG CPLEX Optimization Studio 12.5; IBM ILOG CPLEX for AMPL v12.1; IBM ILOG CPLEX Optimization Studio 12.6; IBM ILOG OPL CPLEX Analyst Studio v6.3.

By default, AMPL uses MINOS as an optimization solver. However, Cplex which was developed by IBM is the most useful solver.

The official website of IBM is not so friendly and they do not remove some web pages which are out of date. To download Cplex, you have to register a academic membership at first. 1) Go to and find the link 'Join now - at no charge'(if the first time) or 'Renew your membership' 2) Then, step 1: you will be asked to Register for a universal IBM ID and password (use your academic email address to do it). Step 2: Complete the Academic Initiative program membership process (click 'apply as a faculty member').

3) After that, you will receive a confirmation email saying the application has been approved. 4) Visit the page, and click the link where is at bottom (This is pretty tricky) 5) After submitting your request, you will go to 'IBM Academic Initiative Software Downloads' page. 6) Type 'cplex' on 'Find by search text' and you will see a list of cplex version choose one and you will see the software list. 7) Since the download needs java applet, you have to enable it for your browser. 8) After the download is finished, you will have a.bin file like 'cplex_studio125.macos.bin'(here I download cplex12.5). DO NOT put it to your Application folder as it is not an application which can be run by your Mac.

9) Put it to some other directory. Open a terminal and find that directory. This bin file is a shell script, so you have to run it by bash. Type and run this command '/bin/bash ~/your/path/cplex_studio125.macos.bin' 10) Follow the instruction and you will install it successfully. 11) Finally, do not forget configure the environment variable for the license: export ILOG_LICENSE_FILE=/your/license/path/access.lim 12) The access.lim is generated from your IBM Academic Initiative.

CPLEX Optimization Studio speeds development and deployment of optimization models, combining leading solver engines with a tightly integrated IDE and modeling language. Speed development and deployment of optimization models, using linear/quadratic, mixed integer, and constraint programming and constraint-based scheduling. Ensure reliable development and maintenance using a transparent modeling language and intuitive tools for model testing, profiling, and tuning. * Solving with mathematical programming: Complete access to a powerful MP solver through the IDE, API, or via third party applications. * Solving with constraint programming: Access to an outstanding and proven CP solver as well, through the IDE, API, or via third party applications.

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