3. Means for solving the task

     The above task of optimizing the customer order in a restaurant or in any other foodservice enterprise is solved by using two multilingual software tools: "Multilingual program of optimization of remote order in a restaurant", version 1.1 (MP OROR 1.1) and "Multilingual program of optimization of order in a restaurant", version 1.2 (MP OOR 1.2). They have been created on the basis of IT AC DTIP by the founder of Technology (all information about it is available at the website "Promotion center of IT AC DTIP"). The tool MP OROR 1.1 is purposed for remote customers of restaurants, which make their advance orders through the Internet, and MP OOR 1.2 — for local customers, making orders at their tables in the restaurant or in their rooms of the hotel with restaurant.

Note 1. These programs are based on the use of language shells of their interfaces which are stored in files. This allows to apply them everywhere, because the user always will be able to select (or create) for yourself a shell of that language in which he usually communicates. Two such shells already exist: Russian and English, and shells for any other languages can be created by users themselves, for which a special utility is provided.

Note 2. MP OROR 1.1 and MP OOR 1.2 are localized versions of the software product of wide application on optimizing expenses LIS/NIS EO 1.2, the last multilingual version 1.3 of which is presented here.

     On the aforesaid website you can do the following:

     You can also buy from the founder of Technology the sets of software utilities ExDb_oror11e and ExDb_oor12e, designed to convert the initial Excel format of the used databases of meals and drinks (DBMDs) to their working format, with binding these utilities via their serial number to technical parameters of that computer on which they will be installed.

     The set of the program MP OROR 1.1 includes 3 solved demo tasks on optimizing the remote order in a restaurant:

     The set of the program MP OOR 1.2 includes 3 solved demo tasks on optimizing the local order in a restaurant: