The Sample Analysis Machine Scheduling Problem: Definition and comparison of exact solving approaches

Nowadays there exists a wide variety of automatic machines that perform analytical tests on liquid samples, such as water, blood, urines, saliva, etc. A test can be modelled set activities with given precedences and through sharing limited resources. scheduling process is therefore required to find feasible or optimal execution tests. An important particularity the performing are their storage areas capacity. For instance, one activity may require sample moved an observation area, while another later remove this from area. In paper, we introduce real problem encountered in instrument industry known Sample Analysis Machine Scheduling Problem (SAMSP). We show SAMSP particular case Resource Constrained Project Cumulative Resources (RCPSP-Cu), present successful application optimization techniques for it. interested exact approaches, since models presented will used prove maximum throughput selected machine layouts. particular, compare performance approaches based Constraint Programming (CP), Satisfiability Modulo Theories (SMT), Mixed Integer Linear (MILP), instances SAMSP.