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In this paper, a multiproduct multiperiod capacitated production system that has been organized as a flow shop is considered. The main novelty of the paper is proposing a more efficient mathematical model for the problem of integrating lot sizing and scheduling with sequence-dependent setups. In comparison to the former model, because of fewer continuous and binary decision variables and constraints in the proposed model, this model is very easier to solve. Comparison between two models proves the superiority of the proposed model. Two mixed integer programming-based approaches with rolling horizon framework have been used to solve this model. To evaluate the performance of the proposed model and solution method, problems of different scales have been studied. The used algorithms search the solution space for both lot-sizing and scheduling problems and find a combination of production planning and scheduling that is feasible and close to optimum. [ABSTRACT FROM AUTHOR]

In this article, different approaches of the use of black box modelling techniques for piezoelectric actuators are particularly addressed, regardless of the employed technique/algorithm. A modelling approach in this paper refers to two matters: the first, the role of black box techniques in modelling (i.e. if physics-based techniques are also involved in modelling; if so, how and to what extent). From this aspect, the spectrum of approaches ranges from those merged with/inspired by classical phenomenological models to an approach based on purely system identification-based techniques. The second aspect of modelling approaches, in this article, is the input variables to the model. Current and previous values of input voltage, previous values of the output (displacement), derivatives and extremum values of the system's input/output have been used as the inputs to the model so far. Both aforementioned aspects of modelling approaches are addressed appropriately in this article, and various modelling approaches in the literature are categorized and presented in a uniform and comparable manner, so that readers can easily identify research trends in this area and the gaps in the literature. One of the identified unanswered questions in the literature is whether the extremum values of the system's input/output should/should not be used as an input to black box models of piezoelectric actuators. There are works in the literature which have/have not used the aforementioned input variables, but there is no published investigation to evidently answer the proposed question. This article, in the last section, answers this question by reporting and discussing an experimental study. [ABSTRACT FROM AUTHOR]

Multiple-route job shop scheduling problem (MRJSP) is a generalization of job shop scheduling problem in which each job may have more than one route for its production and the numbers of operations associated to the alternative routes of the job are not necessarily equal. MRJSP is recognized to be extremely difficult because of its combinatorial nature of integer optimization and the large size of the real problem, necessitating the use of heuristic approaches or dispatching rules for its solution. In this paper, mathematical formulation of MRJSP is first presented. Then, a two-phase algorithm is proposed to deal with the two major sub-problems in MRJSP, namely, the route selection and the sequencing sub-problems. In order to evaluate the effectiveness of the proposed algorithm, several problems (in small, medium, and large sizes) are designed and solved using the proposed algorithm. The problems are also solved using some other dispatching rules, and comparisons are provided. The computational results show that the proposed algorithm generates high-quality schedules in a timely fashion. [ABSTRACT FROM AUTHOR]

This paper analyses different objective functions for the parameter identification of parallel mechanisms and studies the influence in the position and orientation errors to improve their accuracy. A new objective function considering deviation terms is presented. This function is compared with other widely used functions and the advantages and disadvantages of each function are presented. The geometric parameter identification is performed by external calibration by means of the direct kinematic model. First, the objective functions are defined considering error position, error orientation and deviations in measurement. These functions compare the measured and calculated moving platform coordinates in order to obtain the identified model parameters that minimize this difference. The measured coordinates are obtained by measuring three sphere centres, fixed to the moving platform of a parallel mechanism, and the computed coordinates are given by the kinematic model. Second, the model is solved by the Levenberg-Marquardt algorithm for a number of identification positions. Finally, the calibration is verified in test positions. The results obtained show that the consideration of the deviations in measurement in the objective function with respect to classical approaches allows us to better identify those kinematic parameters corresponding with passive joints that cannot be measured. These findings confirm that a suitable objective function can improve the mechanism accuracy by more than one order of magnitude in both position and orientation errors. [ABSTRACT FROM AUTHOR]

This paper addresses the multiple-route job shop scheduling problem to minimize makespan. The problem is recognized to be extremely difficult because of its combinatorial nature of integer optimization and the large size of the real problem. The goal is, thus, to obtain near-optimal schedules in a computationally efficient manner. Mathematical formulation of the problem is first presented. Then, an approach based on artificial immune algorithm is proposed. In order to evaluate the effectiveness of the proposed approach, 30 problems in small, medium, and large size are designed and solved using the proposed approach. Problems are also solved using Lingo software and the results are compared. The computational results show that the proposed approach generates high-quality schedules in a timely fashion. [ABSTRACT FROM AUTHOR]

Given a set of jobs and two batch processing machines (BPMs) arranged in a flow shop environment, the objective is to batch the jobs and sequence the batches such that the makespan is minimized. The job sizes, ready times, and processing times on the two BPMs are known. The batch processing machines can process a batch of jobs as long as the total size of all the jobs assigned to a batch does not exceed its capacity. Once the jobs are batched, the processing time of the batch on the first machine is equal to the longest processing job in the batch; processing time of the batch on the second machine is equal to the sum of processing times of all the jobs in the batch. The batches cannot wait between two machines (i.e., no-wait). The problem under study is NP-hard. We propose a mathematical formulation and present a particle swarm optimization (PSO) algorithm. The solution quality and run time of PSO is compared with a commercial solver used to solve the mathematical formulation. Experimental study clearly highlights the advantages, in terms of solution quality and run time, of using PSO to solve large-scale problems. [ABSTRACT FROM AUTHOR]