To solve the NP-complete no-wait flowshop problems, objective increment properties are analyzed and proved for fundamental operations of heuristics. With these properties, whether a new generated schedule is better or...To solve the NP-complete no-wait flowshop problems, objective increment properties are analyzed and proved for fundamental operations of heuristics. With these properties, whether a new generated schedule is better or worse than the original one is only evaluated by objective increments, instead of completely calculating objective values as the traditional algorithms do, so that the computational time can be considerably reduced. An objective increment-based hybrid genetic algorithm （IGA） is proposed by integrating the genetic algorithm （GA） with an improved various neighborhood search （VNS）as a local search. An initial solution generation heuristic（ISG） is constructed to generate one individual of the initial population. An expectation value-based selection mechanism and a crossover operator are introduced to the mating process. The IGA is compared with the traditional GA and two best-so-far algorithms for the considered problem on 110 benchmark instances. An experimental results show that the IGA outperforms the others in effectiveness although with a little more time consumption.展开更多
A discrete artificial bee colony algorithm is proposed for solving the blocking flow shop scheduling problem with total flow time criterion. Firstly, the solution in the algorithm is represented as job permutation. Se...A discrete artificial bee colony algorithm is proposed for solving the blocking flow shop scheduling problem with total flow time criterion. Firstly, the solution in the algorithm is represented as job permutation. Secondly, an initialization scheme based on a variant of the NEH (Nawaz-Enscore-Ham) heuristic and a local search is designed to construct the initial population with both quality and diversity. Thirdly, based on the idea of iterated greedy algorithm, some newly designed schemes for employed bee, onlooker bee and scout bee are presented. The performance of the proposed algorithm is tested on the well-known Taillard benchmark set, and the computational results demonstrate the effectiveness of the discrete artificial bee colony algorithm. In addition, the best known solutions of the benchmark set are provided for the blocking flow shop scheduling problem with total flow time criterion.展开更多
Production scheduling is one of the most important problems to be considered in the effective performance of the automatic manufacturing system.It is the typical kind of NP-complete problem. The methods commonly used ...Production scheduling is one of the most important problems to be considered in the effective performance of the automatic manufacturing system.It is the typical kind of NP-complete problem. The methods commonly used are not suitable to solve complicated problems because the calculating time rises exponentially with the increase of the problem size. In this paper, a new algorithm - immune based scheduling algorithm (IBSA) is proposed. After the description of the mathematics model and the calculating procedure of immune based scheduling,some examples are tested in the software system called HM IM& C that is developed usingVC+ +6.0. The testing results show that IBSA has high efficiency to solve scheduling problem.展开更多
In this paper, the single machine scheduling problem with release dates and two hierarchical criteria is discussed. The first criterion is to minimize makespan, and the second criterion is to minimize stocking cost. W...In this paper, the single machine scheduling problem with release dates and two hierarchical criteria is discussed. The first criterion is to minimize makespan, and the second criterion is to minimize stocking cost. We show that this problem is strongly NP-hard. We also give an O（n^2） time algorithm for the special case that all stocking costs of jobs in unit time are 1.展开更多
In this paper, an objective-based gradient multi-objective optimization （MOO） technique, the Objective-Based Gradient Algorithm （OBGA）, is proposed with the goal of defining the Pareto domain more precisely and ef...In this paper, an objective-based gradient multi-objective optimization （MOO） technique, the Objective-Based Gradient Algorithm （OBGA）, is proposed with the goal of defining the Pareto domain more precisely and efficiently than current MOO techniques. The performance of the OBGA in locating the Pareto domain was evaluated in terms of precision, computation time and number of objective function calls, and compared to two current MOO algorithms： Dual Population Evolutionary Algorithm （DPEA） and Non-Dominated Sorting Genetic Algorithm I1 （NSGA-II）, using four test problems. For all test problems, the OBGA systematically produced a more precise Pareto domain than DPEA and NSGA-II. With the adequate selection of the OBGA parameters, computation time required for the OBGA can be lower than that required for DPEA and NSGA-II. Results clearly show that the OBGA is a very effective and efficient algorithm for locating the Pareto domain.展开更多
基金The National Natural Science Foundation of China(No.60504029,60672092)the National High Technology Research and Development Program of China(863Program)(No.2008AA04Z103)
文摘To solve the NP-complete no-wait flowshop problems, objective increment properties are analyzed and proved for fundamental operations of heuristics. With these properties, whether a new generated schedule is better or worse than the original one is only evaluated by objective increments, instead of completely calculating objective values as the traditional algorithms do, so that the computational time can be considerably reduced. An objective increment-based hybrid genetic algorithm （IGA） is proposed by integrating the genetic algorithm （GA） with an improved various neighborhood search （VNS）as a local search. An initial solution generation heuristic（ISG） is constructed to generate one individual of the initial population. An expectation value-based selection mechanism and a crossover operator are introduced to the mating process. The IGA is compared with the traditional GA and two best-so-far algorithms for the considered problem on 110 benchmark instances. An experimental results show that the IGA outperforms the others in effectiveness although with a little more time consumption.
基金Supported by the National Natural Science Foundation of China (61174040, 61104178)the Fundamental Research Funds for the Central Universities
文摘A discrete artificial bee colony algorithm is proposed for solving the blocking flow shop scheduling problem with total flow time criterion. Firstly, the solution in the algorithm is represented as job permutation. Secondly, an initialization scheme based on a variant of the NEH (Nawaz-Enscore-Ham) heuristic and a local search is designed to construct the initial population with both quality and diversity. Thirdly, based on the idea of iterated greedy algorithm, some newly designed schemes for employed bee, onlooker bee and scout bee are presented. The performance of the proposed algorithm is tested on the well-known Taillard benchmark set, and the computational results demonstrate the effectiveness of the discrete artificial bee colony algorithm. In addition, the best known solutions of the benchmark set are provided for the blocking flow shop scheduling problem with total flow time criterion.
基金Shanghai Natural Science Foundation (01ZF14004) National Technology Innovation Project (02CJ-14 -05 -01)
文摘Production scheduling is one of the most important problems to be considered in the effective performance of the automatic manufacturing system.It is the typical kind of NP-complete problem. The methods commonly used are not suitable to solve complicated problems because the calculating time rises exponentially with the increase of the problem size. In this paper, a new algorithm - immune based scheduling algorithm (IBSA) is proposed. After the description of the mathematics model and the calculating procedure of immune based scheduling,some examples are tested in the software system called HM IM& C that is developed usingVC+ +6.0. The testing results show that IBSA has high efficiency to solve scheduling problem.
文摘In this paper, the single machine scheduling problem with release dates and two hierarchical criteria is discussed. The first criterion is to minimize makespan, and the second criterion is to minimize stocking cost. We show that this problem is strongly NP-hard. We also give an O（n^2） time algorithm for the special case that all stocking costs of jobs in unit time are 1.
文摘In this paper, an objective-based gradient multi-objective optimization （MOO） technique, the Objective-Based Gradient Algorithm （OBGA）, is proposed with the goal of defining the Pareto domain more precisely and efficiently than current MOO techniques. The performance of the OBGA in locating the Pareto domain was evaluated in terms of precision, computation time and number of objective function calls, and compared to two current MOO algorithms： Dual Population Evolutionary Algorithm （DPEA） and Non-Dominated Sorting Genetic Algorithm I1 （NSGA-II）, using four test problems. For all test problems, the OBGA systematically produced a more precise Pareto domain than DPEA and NSGA-II. With the adequate selection of the OBGA parameters, computation time required for the OBGA can be lower than that required for DPEA and NSGA-II. Results clearly show that the OBGA is a very effective and efficient algorithm for locating the Pareto domain.
