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Job rotation is an organizational strategy increasingly used in manufacturing systems as it provides benefits to both workers and management in an organization. Job rotation prevents musculoskeletal disorders, eliminates boredom and increases job satisfaction and morale. As a result, the company gains a skilled and motivated workforce, which leads to increases in productivity, employee loyalty and decreases in employee turnover. A multi-criteria genetic algorithm is employed to generate job rotation schedules, with considering the most adequate employeejob assignments to prevent musculoskeletal disorders caused by accumulation of fatigue. The algorithm provides the best adequacy available between workers and the competences needed for performing the tasks. The design of the rotation schedules is based not only on ergonomic criteria but also on issues related to product quality and employee satisfaction. The model includes the workers' competences as a measure for the goodness of solutions.

a b s t r a c tWe consider a Distributed Assembly Permutation Flowshop Scheduling Problem with sequence dependent setup times and the objective of makespan minimization. The problem consists of two stages, production and assembly. The first stage comprises f identical factories, where each factory is a flowshop that produces jobs which are later assembled into final products through an identical assembly program in a second assembly stage made by a single machine. Both stages have sequence dependent setup times. This is a realistic and complex problem and therefore, we propose two simple heuristics and two metaheuristics to solve it. A complete calibration and analysis through a Design Of Experiments (DOE) approach is carried out. In the process, important knowledge of the studied problem is obtained as well as some simplifications for the powerful Iterated Greedy methodology which results in a simpler approach with less parameters. Finally, the performance of the proposed methods is compared through extensive computational and statistical experiments.

A novel scheduling problem that results from the addition of resource-assignable setups is presented in this paper. We consider an unrelated parallel machine problem with machine and job sequence dependent setup times. The new characteristic is that the amount of setup time do not only depend on the machine and job sequence, but also on a number of resources assigned, which can vary between a minimum and a maximum. The aim is to give solution to real problems arising in several industries where frequent setup operations in production lines have to be carried out. These operations are indeed setups whose length can be reduced or extended according to the number of resources assigned to them. The objective function considered is a linear combination of total completion time and the total number of resources assigned. We present a MIP model and some fast dispatching heuristics. We carry out careful and comprehensive statistical analyses to study what characteristics of the problem affect the MIP model performance. We also study the effectiveness of the different heuristics proposed.

Abstract:In scheduling, estimations are affected by the imprecision of limited information on future events, and the reduction in the number and level of detail of activities. Overlapping of processes and activities requires the study of their continuity, along with analysis of the risks associated with imprecision. In this line, this paper proposes a fuzzy heuristic model for the Project Scheduling Problem with flows and minimal feeding, time and work Generalized Precedence Relations with a realistic approach to overlapping, in which the continuity of processes and activities is allowed in a discretionary way. This fuzzy algorithm handles the balance of process flows, and computes the optimal fragmentation of tasks, avoiding the interruption of the critical path and reverse criticality. The goodness of this approach is tested on several problems found in the literature; furthermore, an example of a 15-story building was used to compare the better performance of the algorithm implemented in Visual Basic for Applications (Excel) over that same example input in Primavera© P6 Professional V8.2.0, using five different scenarios.