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An Estimation of Distribution Algorithm with Guided Mutation for a Complex Flow Shop Scheduling Problem
"... An Estimation of Distribution Algorithm (EDA) is proposed to approach the Hybrid Flow Shop with Sequence Dependent Setup Times and Uniform Machines in parallel (HFS-SDST-UM) problem. The latter motivated by the needs of a real world company. The proposed EDA implements a fairly new mechanism to impr ..."
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An Estimation of Distribution Algorithm (EDA) is proposed to approach the Hybrid Flow Shop with Sequence Dependent Setup Times and Uniform Machines in parallel (HFS-SDST-UM) problem. The latter motivated by the needs of a real world company. The proposed EDA implements a fairly new mechanism to improve the search of more traditional EDAs. This is the Guided Mutation (GM). EDA-GM generates new solutions by using the information from a probability model, as all EDAs, and the local information from a good known solution. The approach is tested on several instances of HFS-SDST-UM and compared with adaptations of meta-heuristics designed for very similar problems. Encouraging results are reported.
A Distributed Multiobjective Approach to Negotiations in Semi-Competitive Environments
"... Abstract—Realistic negotiation settings in socio-economic contexts are distributed multi-attribute scenarios in which negotiators act largely selfishly but make concessions in the interests of long-term gains. These semi-competitive environments have increasingly complex goal structures in which a s ..."
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Abstract—Realistic negotiation settings in socio-economic contexts are distributed multi-attribute scenarios in which negotiators act largely selfishly but make concessions in the interests of long-term gains. These semi-competitive environments have increasingly complex goal structures in which a single negotiator has difficulty identifying his own ideal goals. In combination with the conflicting goals of other parties to the negotiations, the situation presents itself as a complex multi-objective scenario with incomplete information. Most existing approaches to this problem either assume linear or monotonic functions or they employ an unbiased mediator to select a single proposal as the basis of an agreement. Existing approaches also assume that each negotiating party can identify her own acceptance limit or reservation utility. The current work overcomes these limitations by introducing a distributed approach which integrates another party’s proposals into the local optimisation process. It employs a dynamic coceding strategy which is not dependent on the identification of a reservation utility. I.
to approach the Hybrid Flow Shop with Sequence Dependent
"... Setup Times and Uniform Machines in parallel (HFS-SDST-UM) problem. The latter motivated by the needs of a real world company. The proposed EDA implements a fairly new mechanism to improve the search of more traditional EDAs. This is the Guided Mutation (GM). EDA-GM generates new solutions by using ..."
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Setup Times and Uniform Machines in parallel (HFS-SDST-UM) problem. The latter motivated by the needs of a real world company. The proposed EDA implements a fairly new mechanism to improve the search of more traditional EDAs. This is the Guided Mutation (GM). EDA-GM generates new solutions by using the information from a probability model, as all EDAs, and the local information from a good known solution. The approach is tested on several instances of HFS-SDST-UM and compared with adaptations of meta-heuristics designed for very similar problems. Encouraging results are reported.
Bandit-Inspired Memetic Algorithms for Solving Quadratic Assignment Problems
"... Abstract—In this paper we propose a novel algorithm called the Bandit-Inspired Memetic Algorithm (BIMA) and we have applied it to solve different large instances of the Quadratic Assignment Problem (QAP). Like other memetic algorithms, BIMA makes use of local search and a population of solutions. Th ..."
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Abstract—In this paper we propose a novel algorithm called the Bandit-Inspired Memetic Algorithm (BIMA) and we have applied it to solve different large instances of the Quadratic Assignment Problem (QAP). Like other memetic algorithms, BIMA makes use of local search and a population of solutions. The novelty lies in the use of multi-armed bandit algorithms and assignment matrices for generating novel solutions, which will then be brought to a local minimum by local search. We have compared BIMA to multi-start local search (MLS) and iterated local search (ILS) on five QAP instances, and the results show that BIMA significantly outperforms these competitors.
Effects of Discrete Hill Climbing on Model Building for Estimation of Distribution Algorithms
, 2013
"... Hybridization of global and local searches is a well-known technique for optimization algo-rithms. On estimation of distribution algorithms (EDAs), hill climbing strengthens the signals of dependencies on correlated variables and improves the quality of model building, which re-duces the required po ..."
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Hybridization of global and local searches is a well-known technique for optimization algo-rithms. On estimation of distribution algorithms (EDAs), hill climbing strengthens the signals of dependencies on correlated variables and improves the quality of model building, which re-duces the required population size and convergence time. However, hill climbing also consumes extra computational time. In this paper, analytical models are developed to investigate the effects of combining two different hill climbers with the extended compact genetic algorithm and the dependency structure matrix genetic algorithm. By using the one-max problem and the 5-bit non-overlapping trap problem as the test problems, the performances of different hill climbers are compared. Both analytical models and experiments reveal that the greedy hill climber reduces the number of function evaluations for EDAs to find the global optimum. 1
