We propose the usage of formal languages for expressing instances of NP-complete problems for their application in polynomial transformations. The proposed approach, which consists of using formal language theory for ...We propose the usage of formal languages for expressing instances of NP-complete problems for their application in polynomial transformations. The proposed approach, which consists of using formal language theory for polynomial transformations, is more robust, more practical, and faster to apply to real problems than the theory of polynomial transformations. In this paper we propose a methodology for transforming instances between NP-complete problems, which differs from Garey and Johnson's. Unlike most transformations which are used for proving that a problem is NP-complete based on the NP-completeness of another problem, the proposed approach is intended for extrapolating some known characteristics, phenomena, or behaviors from a problem A to another problem B. This extrapolation could be useful for predicting the performance of an algorithm for solving B based on its known performance for problem A, or for taking an algorithm that solves A and adapting it to solve B.展开更多
In multi-component systems,the components are dependent,rather than degenerating independently,leading to changes inmaintenance schedules.In this situation,this study proposes a grouping dynamicmaintenance strategy.Co...In multi-component systems,the components are dependent,rather than degenerating independently,leading to changes inmaintenance schedules.In this situation,this study proposes a grouping dynamicmaintenance strategy.Considering the structure of multi-component systems,the maintenance strategy is determined according to the importance of the components.The strategy can minimize the expected depreciation cost of the system and divide the system into optimal groups that meet economic requirements.First,multi-component models are grouped.Then,a failure probability model of multi-component systems is established.The maintenance parameters in each maintenance cycle are updated according to the failure probability of the components.Second,the component importance indicator is introduced into the grouping model,and the optimization model,which aimed at a maximum economic profit,is established.A genetic algorithm is used to solve the non-deterministic polynomial(NP)-complete problem in the optimization model,and the optimal grouping is obtained through the initial grouping determined by random allocation.An 11-component series and parallel system is used to illustrate the effectiveness of the proposed strategy,and the influence of the system structure and the parameters on the maintenance strategy is discussed.展开更多
The single machine parallel-batch scheduling with deteriorating jobs and rejection is considered in this paper.A job is either rejected,in which a rejection penalty should be paid,or accepted and processed on the mach...The single machine parallel-batch scheduling with deteriorating jobs and rejection is considered in this paper.A job is either rejected,in which a rejection penalty should be paid,or accepted and processed on the machine.Each job’s processing time is an increasing linear function of its starting time.The machine can process any number of jobs simultaneously as a batch.The processing time of a batch is equal to the largest processing time of the jobs in the batch.The objectives are to minimize the makespan and the total weighted completion time,respectively,under the condition that the total rejection penalty cannot exceed a given upper bound Q.We show that both problems are NP-complete and present dynamic programming algorithms and fully polynomial time approximation schemes(FPTASs)for the considered problems.展开更多
In the theory of computational complexity, the travelling salesman problem is a typical one in the NP class. With the aid of a brand-new approach named “maximum-deleting method”, a fast algorithm is constructed for ...In the theory of computational complexity, the travelling salesman problem is a typical one in the NP class. With the aid of a brand-new approach named “maximum-deleting method”, a fast algorithm is constructed for it with a polynomial time of biquadrate, which greatly reduces the computational complexity. Since this problem is also NP-complete, as a corollary, P = NP is proved to be true. It indicates the crack of the well-known open problem named “P versus NP”.展开更多
The surface-based DNA computing is one of the methods of DNA computing which uses DNA strands immobilized on a solid surface. In this paper, we applied surface-based DNA computing for solving the dominating set proble...The surface-based DNA computing is one of the methods of DNA computing which uses DNA strands immobilized on a solid surface. In this paper, we applied surface-based DNA computing for solving the dominating set problem. At first step, surface-based DNA solution space was constructed by using appropriate DNA strands. Then, by application of a DNA parallel algorithm, dominating set problem was resolved in polynomial time.展开更多
In this paper, the sticker based DNA computing was used for solving the independent set problem. At first, solution space was constructed by using appropriate DNA memory complexes. We defined a new operation called “...In this paper, the sticker based DNA computing was used for solving the independent set problem. At first, solution space was constructed by using appropriate DNA memory complexes. We defined a new operation called “divide” and applied it in construction of solution space. Then, by application of a sticker based parallel algorithm using biological operations, independent set problem was resolved in polynomial time.展开更多
Coloring the nodes of a graph is a commonly used technique to speed up clique search algorithms. Coloring the edges of the graph as a preconditioning method can also be used to speed up computations. In this paper we ...Coloring the nodes of a graph is a commonly used technique to speed up clique search algorithms. Coloring the edges of the graph as a preconditioning method can also be used to speed up computations. In this paper we will show that an unconventional coloring scheme of the edges leads to an NP-complete problem when one intends to determine the optimal number of colors.展开更多
This works aims to give an answer to the problem P = NP? The result is positive with the criteria that solve the Traveling Salesman Problem in polynomial cost of the input size and a proof is given. This problem gets ...This works aims to give an answer to the problem P = NP? The result is positive with the criteria that solve the Traveling Salesman Problem in polynomial cost of the input size and a proof is given. This problem gets a solution because a polyhedron, with a cut flower looking, is introduced instead of graph (e.g. tree).展开更多
A partial order or poset P=(X, on a (finite) base set X?determines the set L(P)?of linear extensions of P. The problem of computing, for a poset P, the cardinality of L(P)?is #P-complete. A set {P1,P2,...,Pk}?of poset...A partial order or poset P=(X, on a (finite) base set X?determines the set L(P)?of linear extensions of P. The problem of computing, for a poset P, the cardinality of L(P)?is #P-complete. A set {P1,P2,...,Pk}?of posets on X?covers the set of linear orders that is the union of the L(Pi). Given linear orders L1,L2,...,Lm on X, the Poset Cover problem is to determine the smallest number of posets that cover {L1,L2,...,Lm}. Here, we show that the decision version of this problem is NP-complete. On the positive side, we explore the use of cover relations for finding posets that cover a set of linear orders and present a polynomial-time algorithm to find a partial poset cover.展开更多
Finding optimal solutions to NP-Hard problems requires exponential time with respect to the size of the problem. Consequently, heuristic methods are usually utilized to obtain approximate solutions to problems of such...Finding optimal solutions to NP-Hard problems requires exponential time with respect to the size of the problem. Consequently, heuristic methods are usually utilized to obtain approximate solutions to problems of such difficulty. In this paper, a novel swarm-based nature-inspired metaheuristic algorithm for optimization is proposed. Inspired by human collective intelligence, Wisdom of Artificial Crowds (WoAC) algorithm relies on a group of simulated intelligent agents to arrive at independent solutions aggregated to produce a solution which in many cases is superior to individual solutions of all participating agents. We illustrate superior performance of WoAC by comparing it against another bio-inspired approach, the Genetic Algorithm, on one of the classical NP-Hard problems, the Travelling Salesperson Problem. On average a 3% - 10% improvement in quality of solutions is observed with little computational overhead.展开更多
文摘We propose the usage of formal languages for expressing instances of NP-complete problems for their application in polynomial transformations. The proposed approach, which consists of using formal language theory for polynomial transformations, is more robust, more practical, and faster to apply to real problems than the theory of polynomial transformations. In this paper we propose a methodology for transforming instances between NP-complete problems, which differs from Garey and Johnson's. Unlike most transformations which are used for proving that a problem is NP-complete based on the NP-completeness of another problem, the proposed approach is intended for extrapolating some known characteristics, phenomena, or behaviors from a problem A to another problem B. This extrapolation could be useful for predicting the performance of an algorithm for solving B based on its known performance for problem A, or for taking an algorithm that solves A and adapting it to solve B.
基金supported by the National Natural Science Foundation of China under Grant No.12172100.
文摘In multi-component systems,the components are dependent,rather than degenerating independently,leading to changes inmaintenance schedules.In this situation,this study proposes a grouping dynamicmaintenance strategy.Considering the structure of multi-component systems,the maintenance strategy is determined according to the importance of the components.The strategy can minimize the expected depreciation cost of the system and divide the system into optimal groups that meet economic requirements.First,multi-component models are grouped.Then,a failure probability model of multi-component systems is established.The maintenance parameters in each maintenance cycle are updated according to the failure probability of the components.Second,the component importance indicator is introduced into the grouping model,and the optimization model,which aimed at a maximum economic profit,is established.A genetic algorithm is used to solve the non-deterministic polynomial(NP)-complete problem in the optimization model,and the optimal grouping is obtained through the initial grouping determined by random allocation.An 11-component series and parallel system is used to illustrate the effectiveness of the proposed strategy,and the influence of the system structure and the parameters on the maintenance strategy is discussed.
基金Supported by the National Natural Science Foundation of China(11871213,71431004).
文摘The single machine parallel-batch scheduling with deteriorating jobs and rejection is considered in this paper.A job is either rejected,in which a rejection penalty should be paid,or accepted and processed on the machine.Each job’s processing time is an increasing linear function of its starting time.The machine can process any number of jobs simultaneously as a batch.The processing time of a batch is equal to the largest processing time of the jobs in the batch.The objectives are to minimize the makespan and the total weighted completion time,respectively,under the condition that the total rejection penalty cannot exceed a given upper bound Q.We show that both problems are NP-complete and present dynamic programming algorithms and fully polynomial time approximation schemes(FPTASs)for the considered problems.
文摘In the theory of computational complexity, the travelling salesman problem is a typical one in the NP class. With the aid of a brand-new approach named “maximum-deleting method”, a fast algorithm is constructed for it with a polynomial time of biquadrate, which greatly reduces the computational complexity. Since this problem is also NP-complete, as a corollary, P = NP is proved to be true. It indicates the crack of the well-known open problem named “P versus NP”.
文摘The surface-based DNA computing is one of the methods of DNA computing which uses DNA strands immobilized on a solid surface. In this paper, we applied surface-based DNA computing for solving the dominating set problem. At first step, surface-based DNA solution space was constructed by using appropriate DNA strands. Then, by application of a DNA parallel algorithm, dominating set problem was resolved in polynomial time.
文摘In this paper, the sticker based DNA computing was used for solving the independent set problem. At first, solution space was constructed by using appropriate DNA memory complexes. We defined a new operation called “divide” and applied it in construction of solution space. Then, by application of a sticker based parallel algorithm using biological operations, independent set problem was resolved in polynomial time.
文摘Coloring the nodes of a graph is a commonly used technique to speed up clique search algorithms. Coloring the edges of the graph as a preconditioning method can also be used to speed up computations. In this paper we will show that an unconventional coloring scheme of the edges leads to an NP-complete problem when one intends to determine the optimal number of colors.
文摘This works aims to give an answer to the problem P = NP? The result is positive with the criteria that solve the Traveling Salesman Problem in polynomial cost of the input size and a proof is given. This problem gets a solution because a polyhedron, with a cut flower looking, is introduced instead of graph (e.g. tree).
文摘A partial order or poset P=(X, on a (finite) base set X?determines the set L(P)?of linear extensions of P. The problem of computing, for a poset P, the cardinality of L(P)?is #P-complete. A set {P1,P2,...,Pk}?of posets on X?covers the set of linear orders that is the union of the L(Pi). Given linear orders L1,L2,...,Lm on X, the Poset Cover problem is to determine the smallest number of posets that cover {L1,L2,...,Lm}. Here, we show that the decision version of this problem is NP-complete. On the positive side, we explore the use of cover relations for finding posets that cover a set of linear orders and present a polynomial-time algorithm to find a partial poset cover.
文摘Finding optimal solutions to NP-Hard problems requires exponential time with respect to the size of the problem. Consequently, heuristic methods are usually utilized to obtain approximate solutions to problems of such difficulty. In this paper, a novel swarm-based nature-inspired metaheuristic algorithm for optimization is proposed. Inspired by human collective intelligence, Wisdom of Artificial Crowds (WoAC) algorithm relies on a group of simulated intelligent agents to arrive at independent solutions aggregated to produce a solution which in many cases is superior to individual solutions of all participating agents. We illustrate superior performance of WoAC by comparing it against another bio-inspired approach, the Genetic Algorithm, on one of the classical NP-Hard problems, the Travelling Salesperson Problem. On average a 3% - 10% improvement in quality of solutions is observed with little computational overhead.
