Complexity of hierarchically and 1-dimensional periodically specified problems

We study the complexity of various combinatorial and satisfiability problems when instances are specified using one of the following specifications: (1) the 1-dimensional finite periodic narrow specifications of Wanke and Ford et al. (2) the 1-dimensional finite periodic narrow specifications with explicit boundary conditions of Gale (3) the 2-way infinite1-dimensional narrow periodic specifications of Orlin et al. and (4) the hierarchical specifications of Lengauer et al. we obtain three general types of results. First, we prove that there is a polynomial time algorithm that given a 1-FPN- or 1-FPN(BC)specification of a graph (or a C N F formula) constructs a level-restricted L-specification of an isomorphic graph (or formula). This theorem along with the hardness results proved here provides alternative and unified proofs of many hardness results proved in the past either by Lengauer and Wagner or by Orlin. Second, we study the complexity of generalized CNF satisfiability problems of Schaefer. Assuming P {ne} PSPACE, we characterize completely the polynomial time solvability of these problems, when instances are specified as in (1), (2),(3) or (4). As applications of our first two types of results, we obtain a number of new PSPACE-hardness and polynomial time algorithms for problems specified as in (1), (2), (3) or(4). Many of our results also hold for O(log N) bandwidth bounded planar instances

Periodically specified satisfiability problems with applications: An alternative to domino problems

We characterize the complexities of several basic generalized CNF satisfiability problems SAT(S), when instances are specified using various kinds of 1- and 2-dimensional periodic specifications. We outline how this characterization can be used to prove a number of new hardness results for the complexity classes DSPACE(n), NSPACE(n), DEXPTIME, NEXPTIME, EXPSPACE etc. The hardness results presented significantly extend the known hardness results for periodically specified problems. Several advantages axe outlined of the use of periodically specified satisfiability problems over the use of domino problems in proving both hardness and easiness results. As one corollary, we show that a number of basic NP-hard problems become EXPSPACE hard when inputs axe represented using 1-dimensional infinite periodic wide specifications. This answers a long standing open question posed by Orlin

Complexity and efficient approximability of two dimensional periodically specified problems

The authors consider the two dimensional periodic specifications: a method to specify succinctly objects with highly regular repetitive structure. These specifications arise naturally when processing engineering designs including VLSI designs. These specifications can specify objects whose sizes are exponentially larger than the sizes of the specification themselves. Consequently solving a periodically specified problem by explicitly expanding the instance is prohibitively expensive in terms of computational resources. This leads one to investigate the complexity and efficient approximability of solving graph theoretic and combinatorial problems when instances are specified using two dimensional periodic specifications. They prove the following results: (1) several classical NP-hard optimization problems become NEXPTIME-hard, when instances are specified using two dimensional periodic specifications; (2) in contrast, several of these NEXPTIME-hard problems have polynomial time approximation algorithms with guaranteed worst case performance

Approximation algorithms for NEXTtime-hard periodically specified problems and domino problems

We study the efficient approximability of two general class of problems: (1) optimization versions of the domino problems studies in [Ha85, Ha86, vEB83, SB84] and (2) graph and satisfiability problems when specified using various kinds of periodic specifications. Both easiness and hardness results are obtained. Our efficient approximation algorithms and schemes are based on extensions of the ideas. Two of properties of our results obtained here are: (1) For the first time, efficient approximation algorithms and schemes have been developed for natural NEXPTIME-complete problems. (2) Our results are the first polynomial time approximation algorithms with good performance guarantees for `hard` problems specified using various kinds of periodic specifications considered in this paper. Our results significantly extend the results in [HW94, Wa93, MH+94]

An SDS Modeling Approach for Simulation-Based Control

We initiate a study of mathematical models for specifying (discrete) simulation-based control systems. It is desirable to specify simulation-based control systems using a model that is intuitive, succinct, expressive, and whose state space properties are relatively easy computationally. We compare automata-based models for specifying control systems and find that all systems that are currently used (such as finite state machines, communicating hierarchical finite state machines (FSM), communicating finite state machines, and Turing machines) lack at least one of the abovementioned features. We propose using sequential dynamical systems (SDS) - a formalism for representing discrete simulations - to specify simulation-based control systems. We show how to adapt the standard SDS model to specify cell-level controllers for a generic cell. For reasonable flexible manufacturing cells, the SDS-based specification has size polynomial in the size of the cell, while in the worst case the FSM-based specification has size exponential in the size of the cell

An SDS Modeling Approach for Simulation-Based Control

We initiate a study of mathematical models for specifying (discrete) simulation-based control systems. It is desirable to specify simulation-based control systems using a model that is intuitive, succinct, expressive, and whose state space properties are relatively easy computationally. We compare automata-based models for specifying control systems and find that all systems that are currently used (such as finite state machines, communicating hierarchical finite state machines (FSM), communicating finite state machines, and Turing machines) lack at least one of the abovementioned features. We propose using sequential dynamical systems (SDS) - a formalism for representing discrete simulations - to specify simulation-based control systems. We show how to adapt the standard SDS model to specify cell-level controllers for a generic cell. For reasonable flexible manufacturing cells, the SDS-based specification has size polynomial in the size of the cell, while in the worst case the FSM-based specification has size exponential in the size of the cell

Level-treewidth property, exact algorithms and approximation schemes

Informally, a class of graphs Q is said to have the level-treewidth property (LT-property) if for every G {element_of} Q there is a layout (breadth first ordering) L{sub G} such that the subgraph induced by the vertices in k-consecutive levels in the layout have treewidth O(f (k)), for some function f. We show that several important and well known classes of graphs including planar and bounded genus graphs, (r, s)-civilized graphs, etc, satisfy the LT-property. Building on the recent work, we present two general types of results for the class of graphs obeying the LT-property. (1) All problems in the classes MPSAT, TMAX and TMIN have polynomial time approximation schemes. (2) The problems considered in Eppstein have efficient polynomial time algorithms. These results can be extended to obtain polynomial time approximation algorithms and approximation schemes for a number of PSPACE-hard combinatorial problems specified using different kinds of succinct specifications studied in. Many of the results can also be extended to {delta}-near genus and {delta}-near civilized graphs, for any fixed {delta}. Our results significantly extend the work in and affirmatively answer recent open questions

Fixpoint logics on hierarchical structures

Hierarchical graph definitions allow a modular description of graphs using modules for the specification of repeated substructures. Beside this modularity, hierarchical graph definitions also allow to specify graphs of exponential size using polynomial size descriptions. In many cases, this succinctness increases the computational complexity of decision problems. In this paper, the model-checking problem for the modal $\mu$-calculus and (monadic) least fixpoint logic on hierarchically defined input graphs is investigated. In order to analyze the modal $\mu$-calculus, parity games on hierarchically defined input graphs are investigated. In most cases precise upper and lower complexity bounds are derived. A restriction on hierarchical graph definitions that leads to more efficient model-checking algorithms is presented