Bilevel Programming, Equilibrium, and Combinatorial Problems with Applications to Engineering
1Department of Systems and Industrial Engineering, ITESM, Campus Monterrey, Monterrey, NL, Mexico
2College of Industrial Engineering, Texas Tech University (TTU), Lubbock, TX, USA
3Universidad Autónoma de Nuevo León, San Nicolás de los Garza, NL, Mexico
4Kharkiv Institute of Banking, University of Banking of the National Bank of Ukraine, Kharkiv, Ukraine
Bilevel Programming, Equilibrium, and Combinatorial Problems with Applications to Engineering
Description
Although many applications fit the bilevel programming (BLP) framework, real-life implementations are scarce, due mainly to the lack of efficient algorithms for tackling medium- and large-scale BLP problems. Solving a BLP problem, even a simplest one, is a difficult task. Many alternative methods may be used, but there is no general method that guarantees convergence or optimality for each problem.
Mixed-integer BLPs (MIBLP) with part of variables being integer are even harder for the conventional optimization techniques. For instance, a replacement of the lower-level (LL) optimization problem with the KKT conditions may fail if some LL variables are not continuous. Therefore, solid theoretical base including elements of combinatorial methods is necessary to propose efficient algorithms aimed at finding local or global solutions of such problems.
Many new applied problems in the energy networks have recently arisen that can be efficiently solved only as MIBLPs: The natural gas cash-out problem, the deregulated electricity market equilibrium problem, biofuel problems, a problem of designing coupled energy carrier networks, etc. Bilevel models to describe migration processes have also become very popular in the area of BLP.
Engineering applications of bilevel optimization and combinatorial problems also include facility location, environmental regulation, energy and agricultural policies, hazardous materials management, and optimal designs for chemical and biotechnological processes.
The primary purpose of the special issue is to discuss these problems with the researchers working in these areas. Potential topics include, but are not limited to:
- Fundamentals of variational inequality theory, BLP, and combinatorial optimization
- Conjectural variations equilibrium and its applications to decision processes
- BLP problems and their reduction to single-level ones
- Logistic problems
- Heuristics for BLP problems
- Equilibrium in models of classical and mixed oligopoly
- Combinatorial problems and the coding theory
- Generalized positional calculus systems: Descriptions and applications in specialized digital devices
- Methods and algorithms for the information coding and compression
Before submission, authors should carefully read over the journal’s Author Guidelines, which are located at http://www.hindawi.com/journals/mpe/guidelines/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/submit/journals/mpe/bp/ according to the following timetable: