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This paper presents a parallel hybrid evolutionary algorithm executed in a grid environment. The algorithm executes local searches using simulated annealing within a Genetic Algorithm to solve the job shop scheduling problem. Experimental results of the algorithm obtained in the ˵Tarantula MiniGrid″ are shown. Tarantula was implemented by linking two clusters from different geographic locations in Mexico (Morelos-Veracruz). The technique used to link the two clusters and configure the Tarantula MiniGrid is described. The effects of latency in communication between the two clusters are discussed. It is shown that the evolutionary algorithm presented is more efficient working in Grid environments because it can carry out major exploration and exploitation of the solution space. [ABSTRACT FROM AUTHOR]

This paper presents the application of a local search algorithm for a logical representation of the Job Shop Scheduling Problem (JSSP). This logical representation represents the JSSP transformed as a satisfiability problem (SAT). The proposed algorithm uses a local search in a wide neighborhood. This algorithm, called Walk Wide Search - SAT, is a variant of the WalkSAT algorithm. This search is possible because the included tabu list prevents an excessive number of repetitions of movements during the search process. This paper describes the algorithm and compares results of Walk Wide Search - SAT to WalkSAT. [ABSTRACT FROM AUTHOR]

This paper presents a new algorithm that obtains an approximation of the Critical Path in schedules generated using the disjunctive graph model that represents the Job Shop Scheduling Problem (JSSP). This algorithm selects a set of operations in the JSSP, where on the average ninety nine percent of the total operations that belong to the set are part of the critical path. A comparison is made of cost and performance between the proposed algorithm, CPA (Critical Path Approximation), and the classic algorithm, CPM (Critical Path Method). With the obtained results, it is demonstrated that the proposed algorithm is very efficient and effective at generating neighborhoods in the simulated annealing algorithm for the JSSP. [ABSTRACT FROM AUTHOR]