A large number of real-world optimization problems can be formulated as Mixed Integer Linear Programs (MILP). MILP solvers expose numerous configuration parameters to control their internal algorithms. Solutions, and associated costs or runtimes, are significantly affected by the choice parameters, even when problem instances have same decision variables constraints. On one hand, using default ...

The scheduling of activities to transport oil derivative products through a pipe network is a complex combinatorial problem that presents a hard computational solution. During the scheduling horizon, many batches are pumped from (or pass through) different areas. Pipes are shared resources. The balance between the demand requirements and the production campaigns, while satisfying inventory mana...

Although recent work in multirobot teaming targets challenging domains such as disaster response or planetary exploration, the lack of formal problem descriptions and benchmarks make it difficult to evaluate various coordination approaches. We formally describe the problem of scheduling a team of robots with heterogeneous capabilities to accomplish a set of joint tasks that are spatially distri...

We consider in this work the problem of scheduling a set of jobs without preemption, where each job requires two resources: (1) a common resource, shared by all jobs, is required during a part of the job’s processing period, while (2) a secondary resource, which is shared with only a subset of the other jobs, is required during the job’s whole processing period. This problem models, for example...

In many real-world hybrid (mixed discrete continuous) planning problems such as Reservoir Control, Heating, Ventilation and Air Conditioning (HVAC), and Navigation, it is difficult to obtain a model of the complex nonlinear dynamics that govern state evolution. However, the ubiquity of modern sensors allow us to collect large quantities of data from each of these complex systems and build accur...

We describe a procedure to reduce variable bounds in Mixed Integer Nonlinear Programming (MINLP) as well as Mixed Integer Linear Programming (MILP) problems. The procedure works by combining pairs of inequalities of a linear programming (LP) relaxation of the problem. This bound reduction technique extends the feasibility based bound reduction technique on linear functions, used in MINLP and MI...

We study valid inequalities for optimizationmodels that contain both binary indicator variables and separable concave constraints. Thesemodels reduce to amixedinteger linear program (MILP) when the concave constraints are ignored, or to a nonconvex global optimization problem when the binary restrictions are ignored. In algorithms designed to solve these problems to global optimality, cutting p...

Mixed integer linear programming (MILP)–based distributed energy management for networked microgrids embedded modern distribution systems is proposed. Considering the diverse ownership of microgrids, resources (DERs) that interface directly with utilities and responsive loads, an alternating direction method multipliers–based framework was formulated scheduling by adjusting nodal price signals ...

One of the main concerns of national statistical agencies (NSAs) is to publish tabular data. NSAs have to guarantee that no private information from specific respondents can be disclosed from the released tables. The purpose of the statistical disclosure control field is to avoid such a leak of private information. Most protection techniques for tabular data rely on the formulation of a large m...