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Abstract: We study an on-line machine covering problem, in which jobs arrive one by one and their processing times are known upon their arrival, and jobs are allowed to migrate between machines when a new job is added in the system. However, the total processing time of migration induced by an incoming job is bounded by a constant factor times the processing time of the incoming job. The objective is to maximize the minimum machine load. In this paper, we present an on-line algorithm with competitive ratio 6/5 for the two identical machines case with . Moreover, the presented on-line algorithm is only a local migration, that is, when one job is assigned to machine , only the jobs on machine are allowed to migrate. We also show that the provided algorithm is a best possible on-line algorithm in the sense of local migration. [Copyright &y& Elsevier]

Abstract: Flexible job-shop scheduling problem (FJSP) is an extension of the classical job-shop scheduling problem. FJSP is NP-hard and mainly presents two difficulties. The first one is to assign each operation to a machine out of a set of capable machines, and the second one deals with sequencing the assigned operations on the machines. This paper proposes a parallel variable neighborhood search (PVNS) algorithm that solves the FJSP to minimize makespan time. Parallelization in this algorithm is based on the application of multiple independent searches increasing the exploration in the search space. The proposed PVNS uses various neighborhood structures which carry the responsibility of making changes in assignment and sequencing of operations for generating neighboring solutions. The results obtained from the computational study have shown that the proposed algorithm is a viable and effective approach for the FJSP. [Copyright &y& Elsevier]

Abstract: We consider in this paper the scheduling of families of jobs in which both processing and delivery are coordinated together. Only one vehicle is available to deliver the jobs to specified customers. The jobs can be processed together to form processing batches on the machine and setups of batches are required when the machine is changing from one family to another. Jobs from different families cannot be transported together by the vehicle. The objective is to minimize the time when the vehicle finishes delivering the last delivery batch to its customer and returns to the machine. We propose an -time optimal algorithm for the scheduling problem under the group technology assumption. For the scheduling problem without the group technology assumption, we show that the problem is NP-hard and give an -time dynamic programming algorithm, where is the number of jobs, and is the number of families; we also provide a heuristic algorithm with a performance ratio of 3/2. [Copyright &y& Elsevier]

Abstract: The recently published edge- and lookup table-based inverse halftoning (ELIH) algorithm has shown its quality and superiority when compared with the previous lookup table-based IH algorithm. This paper presents a new finite state machine model (FSMM)-based search method to speed up the existing ELIH algorithm significantly while preserving the same image quality as in the ELIH algorithm. From the observation that the sliding window for the ELIH algorithm moves from left to right one position; there are therefore one output column and one input column which are introduced at each step and thus a simple finite state machine can track the transitions from the current window movement to the next. This is faster than a full search in the lookup table. Under thirty typical testing images adopted from Meşe’s website, experimental results demonstrated that the proposed FSMM-based ELIH algorithm has an improvement in execution time of 20% to 80%, with a typical improvement of 50%, when compared to the ELIH algorithm. [Copyright &y& Elsevier]

Abstract: We show that the absolute worst case time complexity for Hopcroft’s minimization algorithm applied to unary languages is reached only for deterministic automata or cover automata following the structure of the de Bruijn words. A previous paper by Berstel and Carton gave the example of de Bruijn words as a language that requires steps in the case of deterministic automata by carefully choosing the splitting sets and processing these sets in a FIFO mode for the list of the splitting sets in the algorithm. We refine the previous result by showing that the Berstel/Carton example is actually the absolute worst case time complexity in the case of unary languages for deterministic automata. We show that the same result is valid also for the case of cover automata and an algorithm based on the Hopcroft’s method used for minimization of cover automata. We also show that a LIFO implementation for the splitting list will not achieve the same absolute worst time complexity for the case of unary languages both in the case of regular deterministic finite automata or in the case of the deterministic finite cover automata as defined by S. Yu. [Copyright &y& Elsevier]