Local search algorithms are widely adopted in solving large-scale Distributed Constraint Optimization Problems (DCOPs). However, since each agent always makes its value decision based on the values of its neighbors in local search, those algorithms usually suffer from local premature convergence. More concretely, an agent cannot make a wise decision with poor values of its neighbors since its d...

This paper reports a Fast Local Search (FLS) algorithm which helps to improve the efficiency of hill climbing and a Guided Local Search (GLS) Algorithm which is developed to help local search to escape local optima and distribute search effort. To illustrate how these algorithms work, this paper describes their application to British Telecom’s workforce scheduling problem, which is a hard real ...

This paper reports a Fast Local Search (FLS) algorithm which helps to improve the efficiency of hill climbing and a Guided Local Search (GLS) Algorithm which is developed to help local search to escape local optima and distribute search effort. To illustrate how these algorithms work, this paper describes their application to British Telecom’s workforce scheduling problem, which is a hard real ...

| The combination of local search heuristics and genetic algorithms is a promising approach for nding near-optimum solutions to the traveling salesman problem (TSP). In this paper, an approach is presented in which local search techniques are used to nd local optima in a given TSP search space, and genetic algorithms are used to search the space of local optima in order to nd the global optimum...

Corresonding author: Dr. B. Wade Brorsen, Oklahoma State University, Department of Agricultural Economics, 414 Ag Hall, 74078; [email protected], ph. 405-744-6155. Abstract – The training of neural networks is a difficult optimization problem because of the nonconvex objective function. Therefore, as an alternative to local search search algorithms, many global search algorithms have been use...

Most former studies of Distributed Constraint Optimization Problems (DisCOPs) search considered only complete search algorithms, which are practical only for relatively small problems. Distributed local search algorithms can be used for solving DisCOPs. However, because of the differences between the global evaluation of a system’s state and the private evaluation of states by agents, agents ar...

The Flexible Job Shop Scheduling Problem (FJSP) is one of the most general and difficult of all traditional scheduling problems. The Flexible Job Shop Problem (FJSP) is an extension of the classical job shop scheduling problem which allows an operation to be processed by any machine from a given set. The problem is to assign each operation to a machine and to order the operations on the machine...

Most former studies of Distributed Constraint Optimization Problems (DisCOPs) search considered only complete search algorithms, which are practical only for relatively small problems. Distributed local search algorithms can be used for solving DisCOPs. However, because of the differences between the global evaluation of a system’s state and the private evaluation of states by agents, agents ar...