Jarosław Pempera

Sequencing of jobs in some production system

Abstract We consider a real-life problem of scheduling clients orders in the production of concrete blocks in a factory of building industry. This problem can be modelled as a hybrid flow shop scheduling problem with mixed no-wait/no-store constraints and mixed bottleneck/non-bottleneck machines. The objective function is to minimize maximum completion time. To solve the problem, we propose an approximation algorithm based on the tabu search approach.

Some local search algorithms for no-wait flow-shop problem with makespan criterion

This paper develops and compares different local search algorithms for the no-wait flow-shop problem with makespan criterion (Cmax). We present several variants of descending search and tabu search algorithms. In the algorithms the multimoves are used that consist in performing several moves simultaneously in a single iteration of algorithm and allow us to accelerate the convergence to good solutions. Besides, in the tabu search algorithms a dynamic tabu list is proposed that assists additionally to avoid trapped at a local optimum. The proposed algorithms are empirically evaluated and found to be relatively more effective in finding better quality solutions than existing algorithms. The presented ideas can be applied in any local search procedures.

Parallel tabu search algorithm for the hybrid flow shop problem

The paper deals with the parallel variant of the scheduling algorithm dedicated to the hybrid flow shop problem. The problem derives from practice of automated manufacturing lines, e.g. for printed packages. The overall goal is to design a new algorithm which merges the performance of the best known sequential approach with the efficient exploitation of parallel calculation environments. In order to fulfill the above aim, there are two methods proposed in this paper: the original fast method of parallel calculation of the criterion function and the local neighborhood parallel search method embedded in the tabu search approach. The theoretical analysis, as well as the original implementation, with the use of vector processing instructions SSE2 supported by suitable data organization, are presented below. Numerical properties of the proposed algorithm are empirically verified on the multi-core processor.

Parallel Simulated Annealing for the Job Shop Scheduling Problem

This paper describes two parallel simulated annealing algorithms for the job shop scheduling problem with the sum of job completion times criterion. Some properties of the problem associated with the block theory have been presented and discussed. These properties allow us to introduce the effective neighborhood based on the adjacent swap type moves. In this paper, an original method for parallel calculation of optimization criterion value for set of solutions, recommended for the use in metaheuristics with single- and multiple- search trajectories is proposed. Additionally, the vector calculation method, that uses multiple mathematical instructions MMX supported by suitable data organization, is presented. Properties of parallel calculations are empirically verified on the PC with Intel Core 2 Duo processor on Taillards benchmarks.

Parallel Simulated Annealing Algorithm for Cyclic Flexible Job Shop Scheduling Problem

This paper deals with scheduling of tasks in cyclic flexible job shop scheduling problem (CFJSSP). We have proposed a new method of computing cyclic time for CFJSSP. This method is based on the known properties of the job shop problem as well as new properties of cyclic scheduling. We have developed two versions of proposed method: sequential and parallel. The parallel version is dedicated to the computing devices supporting vector processing. Finally, we have developed double paralyzed simulated annealing algorithms: fine grained - vector processing, multiple walk - multi core processing. Computation results, provided on market multicore processors, are presented for a set of benchmark instances from the literature.

A new approach for multi-criteria scheduling

Display Omitted We use a Enhanced SA algorithm for bi-criteria permutation flow shop problem.We consider vector processing to improve computational time of the algorithm.Implementation of VESA is achieved even on single thread processors.Considerable increase in number of evaluated solutions per unit of time is observed.Better approximation of the Pareto frontier is obtained. In this paper we propose a new approach, recommended for solving certain class of multi-criteria scheduling problems, with the use of cloud exploration of the solution space supported by fine-grained parallel computing. The approach allow us to approximate Pareto front more accurately than other known algorithms in competitive time. To show and check advantageous properties of the proposed approach, the new solution algorithm, called VESA, was implemented for the case of bi-criteria flow shop scheduling problem and tested against a number of high-quality benchmarks known in the literature. Vector processing technologies are used to enhance the efficiency of solution search and acceptance rates for the extended simulated annealing metaheuristic. Results are compared using, among others, the independent Hyper-Volume Indicator ( I H ) measure. Computer test of VESA confirms excellent approximation of the Pareto front.

Scheduling in Production of Concrete Wares

We consider a real-life problem of scheduling clients orders in the production of concrete wares in a factory of building industry. This problem can be modeled as hybrid flow shop scheduling problem with mixed no wait/no store constraints and the makespan criterion. To solve the problem, we propose an approximation algorithm based on the tabu search approach.

Cyclic Hybrid Flow-shop Scheduling Problem with Machine Setups☆

Abstract In this paper we consider an NP -hard hybrid flow shop problem with machine setups and cycle-time minimization. The above issue is an important generalization of a flow-shop problem with minimization of a cycle time, and it stays in a direct relationship with a flexible job shop problem. In the hybrid problem task operations are performed by machines arranged in slots, i.e., a set of machines with the same functional properties. In this work we presented a graph model, properties of the problem and methods of determining approximate value of the optimal cycle duration. The above mentioned concepts have been used in the construction of tabu search algorithm. Computational experiments were conducted on well-known in literature examples, which confirmed high efficiency of the algorithm.

Parallel tabu search for the cyclic job shop scheduling problem

Abstract In this paper, we consider a cyclic job shop problem, consisting of production of a certain set of elements at fixed intervals. Optimization of the process is reduced to a minimization of a cycle time, i.e. the time, after which the next batch of the same elements may be produced. We introduce a new parallel method for the cost function calculation. The parallelization is not trivial and cannot be done automatically by the existing compilers due to the recurrent character of formulas. Since the problem is strongly NP-hard, a heuristic algorithm was designed to solve it. Computational experiments were done in a multiprocessor environment, namely – in Intel Xeon Phi.

Parallel tabu search algorithm for the permutation flow shop problem with criterion of minimizing sum of job completion times

This paper deals with an intelligent algorithm dedicated for the use in manufacturing systems. Particularly, it develops the fast parallel tabu search algorithm to minimize sum of job completion times in the flow shop scheduling problem. So called multimoves are used, that consist in performing several independent moves simultaneously, which allow one to guide very quickly the search process to promising areas of the solutions space, where good solutions can be found. Besides, an adaptable dynamic tabu list and varying neighborhood are proposed to avoid being trapped at a local optimum. The proposed algorithms are experimentally evaluated on a personal computer with duo-core processor and found to be relatively more effective in finding solutions of quality better than other leading approaches, and also it makes in a much shorter time. The presented ideas can be extended to cover search methods for other hard problems.