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2021, vol. 76, br. 2, str. 239-245
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Organizacija rada sa klijentima u vanrednim uslovima COVID-19 uz pomoć programiranja sa ograničenjima
Organization of work with clients in the COVID-19 emergency conditions using constraint programming
Sažetak
U realnim uslužnim i proizvodnim sistemima često se javlja potreba donošenja odluka koje se tiču alokacije ograničenog broja vrsta i ograničene količine različitih resursa tokom vremena, u okviru zadatih aktivnosti, uz optimizaciju zadate funkcije cilja. Resursi mogu biti ljudi, mašine, sirovine, učionice i sl. Aktivnosti su skupovi operacija u nekom proizvodnom ili uslužnom procesu, kao što su ispiti, rad na mašini i sl. Alokacija resursa predstavlja problem od velikog praktičnog značaja kojim su se duže vreme bavili naučnici iz oblasti operacionih istraživanja. Matematički, alokacija resursa predstavlja problem optimizacije, gde su ograničenja u potpunosti poznata, kriterijum optimizacije jasno i tačno definisan, a sve se to odigrava u predvidljivim uslovima. Razvoj potpuno automatizovanih sistema za rešavanje problema alokacije se često odbacuje od strane krajnjih korisnika. Razlog mogu predstavljati ograničenja koja je, često, teško u potpunosti registrovati, kriterijume za odlučivanje je teško odrediti, a korisnici nisu eksperti u korišćenju kompleksnih matematičkih koncepata kao što su velike matrice matematičkog programiranja ili težinski faktori višekriterijumske optimizacije.
Abstract
In real service and production systems, there is often a need to make decisions regarding allocation of limited number of types and amounts of different resources over time, within the given activities, with the optimization of the given goal function. Resources can be people, machines, raw materials, classrooms etc. Activities are sets of operations in a production or service process, such as exams, machine work etc. Resource allocation is a problem of great practical importance that has long been addressed by scientists in the field of operational research. Mathematically, resource allocation is an optimization problem, where the limitations are fully known, the optimization criteria are clearly and precisely defined and all this takes place in predictable conditions. The development of fully automated systems for solving allocation problems is often rejected by end users. The reason may be limitations that are often difficult to fully register, decision criteria are difficult to determine, and users are not experts in using complex mathematical concepts such as large matrices of mathematical programming or weighting factors of multicriteria optimization.
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