A new polynomial-time algorithm for linear programming
Combinatorica
Combinatorial optimization: algorithms and complexity
Combinatorial optimization: algorithms and complexity
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Membrane Computing: An Introduction
Membrane Computing: An Introduction
Linear Programming in O([n3/ln n]L) Operations
SIAM Journal on Optimization
Membrane Computing: When Communication Is Enough
UMC '02 Proceedings of the Third International Conference on Unconventional Models of Computation
Applications of Membrane Computing (Natural Computing Series)
Applications of Membrane Computing (Natural Computing Series)
Computational Complexity of Simple P Systems
Fundamenta Informaticae
Uniform solution of QSAT using polarizationless active membranes
MCU'07 Proceedings of the 5th international conference on Machines, computations, and universality
An approach to computational complexity in membrane computing
WMC'04 Proceedings of the 5th international conference on Membrane Computing
On descriptive complexity of p systems
WMC'04 Proceedings of the 5th international conference on Membrane Computing
Evolving by maximizing the number of rules: complexity study
WMC'09 Proceedings of the 10th international conference on Membrane Computing
| Hi-index | 0.00 |
We introduce a variant of P systems called maximum cooperative P systems; it consists of transition P systems with cooperative rules that evolve at each step by consuming the maximum number of objects. The problem of distributing objects to rules in order to achieve a maximum consuming evolution is studied by introducing the resource mapping problem. The decision version of this optimization problem is proved to be NP-complete. We describe a new simulation technique for the evolution of the maximum cooperative P systems based on integer linear programming. Finally we illustrate the evolution by an example.