Abstract We will describe our ongoing work in theWe will describe our ongoing work in the eld of optimal scheduling for real time systems We are primarily concerned with optimal task allocation and job scheduling for parallel computer systems Many real time task allocation and job scheduling problems are proven to be NP hard Recently we proposed a random ized optimization framework for e cientl...

We show that if NP , co−RP then the existence of efficient indistinguishability obfuscation (iO) implies the existence of one-way functions. Thus, if we live in “Pessiland”, where NP problems are hard on the average but one-way functions do not exist, or even in “Heuristica”, where NP problems are hard in the worst case but easy on average, then iO is impossible. Our result makes it redundant t...

We introduce networks with additive losses and gains on the arcs. If a positive flow of x units enter an arc a, then x + g(a) units exit. Arcs may increase or consume flow, i.e., they are gainy or lossy. Such networks have various applications, e.g., in financial analysis, transportation, and data communication. Problems in such networks are generally intractable. In particular, the shortest pa...

Flow shop sequencing problem is included in NP-hard problems and a number of heuristic methods have been developed to solve it. Most of these methods are offered for the crisp processing time. However fuzzy algorithm is appropriate for the problems with fuzzy processing time. This paper presents a method in which an algorithm is used to minimize make span of flow shop with fuzzy processing time...

NP-hard problems occur often in bioinformatics. The typical huge sizes of biological problem instances often prohibit solving NP-hard problems in bioinformatics optimally with classical approaches. Fixed-parameterized algorithmics has been developed in 1990s as a new approach to solve NP-hard problem optimally in a guaranteed running time. The essential idea of fixed-parameter algorithms is to ...

We analyze the run-time complexity of computing allocations that are both fair and maximize utilitarian social welfare, defined as sum agents’ utilities. focus on two tractable fairness concepts: envy-freeness up to one item (EF1) proportionality (PROP1). consider computational problems: (1) Among utilitarian-maximal allocations, decide whether there exists is also fair; (2) among compute maxim...

Scheduling problems are important NP-hard problems. Genetic algorithms can provide good solutions for such optimization problems. In this paper, we present a genetic algorithm to solve the single machine total weighted tardiness scheduling problem, which is a strong NP-hard problem. The algorithm uses the natural permutation representation of a chromosome, heuristic dispatching rules combined w...

Optimization problems frequently appear in any scientific domain. Most of the times, corresponding decision problem turns out to be NP-hard, and these cases genetic algorithms are often used obtain approximated solutions. However, difficulty approximate different NP-hard can vary a lot. In this paper, we analyze usefulness using depending on approximation class belongs to. particular, use stand...

It has previously been proven that finding the globally minimum energy configuration of an atomic cluster belongs in the class of NP-hard problems. However, this proof is limited only to homonuclear clusters. This paper presents a new proof which shows finding minimum energy configurations for heteronuclear clusters is also NP-hard.

It has become increasingly apparent this last decade that many problems in systems and control are NP-hard and, in some cases, undecidable. The inherent complexity of some of the most elementary problems in systems and control points to the necessity of using alternative approximate techniques to deal with problems that are unsolvable or intractable when exact solutions are sought. We survey so...