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Reha Uzsoy - One of the best experts on this subject based on the ideXlab platform.

  • a genetic algorithm for minimizing maximum lateness on parallel identical Batch Processing machines with dynamic job arrivals and incompatible job families
    Computers & Operations Research, 2007
    Co-Authors: Sujay Malve, Reha Uzsoy
    Abstract:

    We consider the problem of minimizing maximum lateness on parallel identical Batch Processing machines with dynamic job arrivals. We propose a family of iterative improvement heuristics based on previous work by Potts [Analysis of a heuristic for one machine sequencing with release dates and delivery times. Operations Research 1980;28:1436-41] and Uzsoy [Scheduling Batch Processing machines with incompatible job families. International Journal for Production Research 1995;33(10):2685-708] and combine them with a genetic algorithm (GA) based on the random keys encoding of Bean [Genetic algorithms and random keys for sequencing and optimization. ORSA Journal on Computing 1994;6(2):154-60]. Extensive computational experiments show that one of the proposed GAs runs significantly faster than the other, providing a good tradeoff between solution time and quality. The combination of iterative heuristics with GAs consistently outperforms the iterative heuristics on their own.

  • a genetic algorithm to minimize maximum lateness on a Batch Processing machine
    Computers & Operations Research, 2002
    Co-Authors: Chengshuo Wang, Reha Uzsoy
    Abstract:

    We consider the problem of minimizing maximum lateness on a Batch Processing machine in the presence of dynamic job arrivals. The Batch Processing machine can process up to B jobs simultaneously, and the Processing time of a Batch is given by that of the job with the longest Processing time in the Batch. We adapt a dynamic programming algorithm from the literature to determine whether a due-date feasible Batching exists for a given job sequence. We then combine this algorithm with a random keys encoding scheme to develop a genetic algorithm for this problem. Computational experiments indicate that this algorithm has excellent average performance with reasonable computational burden.

  • minimizing makespan on a single Batch Processing machine with dynamic job arrivals
    International Journal of Production Research, 1999
    Co-Authors: Chung Yee Lee, Reha Uzsoy
    Abstract:

    We consider the problem of minimizing makespan Cmax on a single Batch Processing machine in the presence of dynamic job arrivals. The Batch Processing machine can process up to B jobs simultaneously. The Processing time of a Batch is given by the Processing time of the longest job in the Batch. We present polynomial and pseudopolynomial-time algorithms for several special cases, develop efficient heuristics for the general problem and evaluate their performance through extensive computational experiments. Our results indicate that several of the heuristics have an excellent average performance with a modest computational burden.

  • minimizing total tardiness on a Batch Processing machine with incompatible job families
    Iie Transactions, 1998
    Co-Authors: Sanjay Mehta, Reha Uzsoy
    Abstract:

    Abstract Motivated by an application in semiconductor manufacturing, we study the problem of minimizing total tardiness on a Batch Processing machine with incompatibl8e job families, where all jobs of the same family have identical Processing times and jobs of different families cannot be processed together. We present a dynamic programming algorithm which has polynomial time complexity when the number of job families and the Batch machine capacity are fixed. We also examine various heuristic solution procedures which can provide near optimal solutions in a reasonable amount of computation time.

  • scheduling Batch Processing machines with incompatible job families
    International Journal of Production Research, 1995
    Co-Authors: Reha Uzsoy
    Abstract:

    The problem of scheduling a single Batch Processing machine with incompatible job families was studied, where jobs of different families cannot be processed together in the same Batch. First static problems where all jobs are available simultaneously were considered and showed that for a regular performance measure there will be no unnecessary partial Batches. This allowed us to develop efficient optimal algorithms to minimize makespan (Cmax), maximum lateness (Lmax) and total weighted completion time and apply some of these results to problems with parallel identical Batch Processing machines. Then problems withdynamic job arrivals were considered and an efficient optimal algorithm for minimizing Cmax and several heuristics to minimize Lmax were provided. Computational experiments showed that the heuristics developed for the latter problem consistently improve on dispatching solutions in very reasonable CPU times.

Chung Yee Lee - One of the best experts on this subject based on the ideXlab platform.

  • minimizing makespan on a single Batch Processing machine with nonidentical job sizes
    Naval Research Logistics, 2001
    Co-Authors: Guochuan Zhang, Chung Yee Lee, Xiaoqiang Cai, C K Wong
    Abstract:

    We deal with the problem of minimizing makespan on a single Batch Processing machine. In this problem, each job has both Processing time and size (capacity requirement). The Batch Processing machine can process a number of jobs simultaneously as long as the total size of these jobs being processed does not exceed the machine capacity. The Processing time of a Batch is just the Processing time of the longest job in the Batch. An approximation algorithm with worst-case ratio 3/2 is given for the version where the Processing times of large jobs (with sizes greater than 1/2) are not less than those of small jobs (with sizes not greater than 1/2). This result is the best possible unless P = NP. For the general case, we propose an approximation algorithm with worst-case ratio 7/4. A number of heuristics by Uzosy are also analyzed and compared. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 226–240, 2001

  • minimizing makespan on a single Batch Processing machine with dynamic job arrivals
    International Journal of Production Research, 1999
    Co-Authors: Chung Yee Lee, Reha Uzsoy
    Abstract:

    We consider the problem of minimizing makespan Cmax on a single Batch Processing machine in the presence of dynamic job arrivals. The Batch Processing machine can process up to B jobs simultaneously. The Processing time of a Batch is given by the Processing time of the longest job in the Batch. We present polynomial and pseudopolynomial-time algorithms for several special cases, develop efficient heuristics for the general problem and evaluate their performance through extensive computational experiments. Our results indicate that several of the heuristics have an excellent average performance with a modest computational burden.

  • scheduling with agreeable release times and due dates on a Batch Processing machine
    European Journal of Operational Research, 1997
    Co-Authors: Chung Yee Lee
    Abstract:

    Abstract We consider the problem of scheduling semiconductor burn-in operations, where burn-in ovens are modeled as Batch Processing machines. The job release times and due dates are assumed to be agreeable. Two different objective functions are considered: minimize the maximum tardiness and minimize the number of tardy jobs. We study the complexity of the problems. Efficient algorithms are also provided for the case when the job release times, due dates, and Processing times are agreeable, which generalize those provided by Lee, Uzsoy and Martin-Vega (1992).

  • minimizing total completion time on Batch Processing machines
    International Journal of Production Research, 1993
    Co-Authors: Vijay Chandru, Chung Yee Lee, Reha Uzsoy
    Abstract:

    We study the problem of minimizing total completion time on single and parallel Batch Processing machines. A Batch Processing machine is one which can process up to B jobs simultaneously. The Processing time of a Batch is equal to the largest Processing time among all jobs in the Batch. This problem is motivated by burn-in operations in the final testing stage of semiconductor manufacturing and is expected to occur in other production environments. We provide an exact solution procedure for the single-machine problem and heuristic algorithms for both single and parallel machine problems. While the exact algorithms have limited applicability due to high computational requirements, extensive experiments show that the heuristics are capable of consistently obtaining near-optimal solutions in very reasonable CPU times.

  • minimizing total completion time on a Batch Processing machine with job families
    Operations Research Letters, 1993
    Co-Authors: Vijay Chandru, Chung Yee Lee, Reha Uzsoy
    Abstract:

    We consider the problem of minimizing the total completion time on a single Batch Processing machine. The set of jobs to be scheduled can be partitioned into a number of families, where all jobs in the same family have the same Processing time. The machine can process at most B jobs simultaneously as a Batch, and the Processing time of a Batch is equal to the Processing time of the longest job in the Batch. We analyze that properties of an optimal schedule and develop a dynamic programming algorithm of polynomial time complexity when the number of job families is fixed. The research is motivated by the problem of scheduling burn-in ovens in the semiconductor industry.

Purushothaman Damodaran - One of the best experts on this subject based on the ideXlab platform.

  • A particle swarm optimization algorithm for minimizing makespan of nonidentical parallel Batch Processing machines
    The International Journal of Advanced Manufacturing Technology, 2012
    Co-Authors: Purushothaman Damodaran, Don Asanka Diyadawagamage, Omar Ghrayeb, Mario C. Vélez-gallego
    Abstract:

    This research is motivated by our interactions with an electronics manufacturer who assembles and tests printed circuit boards (PCBs) used in consumer products. Environmental stress screening (ESS) chambers are commonly used to test PCBs to detect early failures before they are used in the field. The chambers are capable of testing multiple PCBs simultaneously (i.e., Batch Processing machines). The minimum testing time of each PCB and their size are known. The objective is to group these PCBs into Batches and schedule the Batches formed on ESS chambers such that the makespan is minimized. The ESS chambers can process a Batch of jobs as long as its capacity is not violated. Each ESS chamber is unique with respect to its capacity. The problem is NP-hard. Consequently, a particle swarm optimization (PSO) algorithm is proposed. The effectiveness of the PSO algorithm is evaluated by comparing its results to a random-key genetic algorithm and a commercial solver used to solve a mixed-integer linear program. A thorough experimental study conducted indicates that the PSO algorithm reports better quality solution in a short time on larger problem instances.

  • a simulated annealing algorithm to minimize makespan of parallel Batch Processing machines with unequal job ready times
    Expert Systems With Applications, 2012
    Co-Authors: Purushothaman Damodaran, Mario C Velezgallego
    Abstract:

    A simulated annealing (SA) algorithm to minimize the makespan on a group of identical Batch Processing machines arranged in parallel is presented. We consider the case where each job has an arbitrary Processing time, non-identical size, and non-zero ready time. Each machine can process simultaneously several jobs as a Batch as long as the machine capacity is not exceeded. The Batch Processing time is equal to the largest Processing time among those jobs in the Batch. Similarly, the Batch ready time is equal to the largest ready time among all the jobs in the Batch. Random instances were used to compare the results of the SA approach against a lower bound, a mathematical model, and two heuristics published in the literature: the Modified Delay (MD) heuristic and a Greedy Randomized Adaptive Search Procedure (GRASP). Computational experiments showed that the SA approach is comparable to GRASP with respect to solution quality, and less computationally costly. Both SA and GRASP comfortably outperformed the MD heuristic.

  • a grasp approach for makespan minimization on parallel Batch Processing machines
    Journal of Intelligent Manufacturing, 2011
    Co-Authors: Purushothaman Damodaran, Mario C Velezgallego, Jairo Maya
    Abstract:

    In this paper we consider the problem of scheduling a set of identical Batch Processing machines arranged in parallel. A Greedy Randomized Adaptive Search Procedure (GRASP) approach is proposed to minimize the makespan under the assumption of non-zero job ready times, arbitrary job sizes and arbitrary Processing times. Each machine can process simultaneously several jobs as a Batch as long as the machine capacity is not violated. The Batch Processing time is equal to the largest Processing time among those jobs in the Batch. Similarly, the Batch ready time is equal to the largest ready time among those jobs in the Batch. The performance of the proposed GRASP approach was evaluated by comparing its results to a lower bound and heuristics published in the literature. Experimental study suggests that the solution obtained from the GRASP approach is superior compared to other heuristics.

  • Heuristics to minimize makespan of parallel Batch Processing machines
    The International Journal of Advanced Manufacturing Technology, 2008
    Co-Authors: Purushothaman Damodaran, Ping-yu Chang
    Abstract:

    Batch-Processing machines can process several jobs simultaneously. These machines are commonly used to test Printed Circuit Boards (PCBs). The Processing time and the dimensions of the PCB are given. Each Batch is formed such that the total size of all the PCBs in the Batch does not exceed the machine capacity. The Batch Processing time is equal to the longest Processing time of all the PCBs in the Batch. These Batch Processing machines are expensive and a bottleneck. Scheduling PCBs on these parallel Batch Processing machines to minimize their makespan is NP-hard. Consequently, we propose several heuristics. The performance of the proposed heuristics is compared to a simulated annealing approach and a commercial solver.

  • minimizing makespan on a Batch Processing machine with non identical job sizes using genetic algorithms
    International Journal of Production Economics, 2006
    Co-Authors: Purushothaman Damodaran, Praveen Kumar Manjeshwar, K Srihari
    Abstract:

    Abstract This paper aims at minimizing the makespan for a Batch-Processing machine. The Processing times and the sizes of the jobs are known. The machine can process a Batch as long as its capacity is not exceeded. The Processing time of a Batch is the longest Processing time of all the jobs in that Batch. This problem is NP-hard and hence a genetic algorithm (GA) approach is proposed. Random instances were used to test the effectiveness of the proposed approach. The results obtained from GA were compared with a simulated annealing approach and a commercial solver. The results indicate that the GA was able to arrive at better makespan with shorter run times.

Ping-yu Chang - One of the best experts on this subject based on the ideXlab platform.

  • Heuristics to minimize makespan of parallel Batch Processing machines
    The International Journal of Advanced Manufacturing Technology, 2008
    Co-Authors: Purushothaman Damodaran, Ping-yu Chang
    Abstract:

    Batch-Processing machines can process several jobs simultaneously. These machines are commonly used to test Printed Circuit Boards (PCBs). The Processing time and the dimensions of the PCB are given. Each Batch is formed such that the total size of all the PCBs in the Batch does not exceed the machine capacity. The Batch Processing time is equal to the longest Processing time of all the PCBs in the Batch. These Batch Processing machines are expensive and a bottleneck. Scheduling PCBs on these parallel Batch Processing machines to minimize their makespan is NP-hard. Consequently, we propose several heuristics. The performance of the proposed heuristics is compared to a simulated annealing approach and a commercial solver.

  • minimizing makespan on parallel Batch Processing machines
    International Journal of Production Research, 2004
    Co-Authors: Ping-yu Chang, Purushothaman Damodaran, Sharif H Melouk
    Abstract:

    A simulated annealing approach to minimize makespan for identical parallel Batch-Processing machines is presented. Each job has a corresponding Processing time and size. The machine can process the jobs in Batches as long as the total size of all the jobs in a Batch does not exceed the machine capacity. The Processing time of a Batch is equal to the longest Processing time among all the jobs in the Batch. Random instances were generated to test the approach with respect to solution quality and run time. The results of the simulated annealing approach were compared with CPLEX. The approach outperforms CPLEX on most of the instances.

  • minimizing makespan for single machine Batch Processing with non identical job sizes using simulated annealing
    International Journal of Production Economics, 2004
    Co-Authors: Sharif H Melouk, Purushothaman Damodaran, Ping-yu Chang
    Abstract:

    Abstract This research proposes a simulated annealing (SA) approach to minimize makespan for a single Batch-Processing machine. Each job has a corresponding Processing time and size. The machine can process the jobs in Batches as long as the machine capacity is not exceeded. The Processing time of a Batch is equal to the longest Processing time among all jobs in the Batch. Random instances were generated to test our approach with respect to solution quality and run time. The results of the SA approach were compared to CPLEX. Our approach outperforms CPLEX on all the instances.

Sharif H Melouk - One of the best experts on this subject based on the ideXlab platform.

  • minimizing makespan on parallel Batch Processing machines
    International Journal of Production Research, 2004
    Co-Authors: Ping-yu Chang, Purushothaman Damodaran, Sharif H Melouk
    Abstract:

    A simulated annealing approach to minimize makespan for identical parallel Batch-Processing machines is presented. Each job has a corresponding Processing time and size. The machine can process the jobs in Batches as long as the total size of all the jobs in a Batch does not exceed the machine capacity. The Processing time of a Batch is equal to the longest Processing time among all the jobs in the Batch. Random instances were generated to test the approach with respect to solution quality and run time. The results of the simulated annealing approach were compared with CPLEX. The approach outperforms CPLEX on most of the instances.

  • minimizing makespan for single machine Batch Processing with non identical job sizes using simulated annealing
    International Journal of Production Economics, 2004
    Co-Authors: Sharif H Melouk, Purushothaman Damodaran, Ping-yu Chang
    Abstract:

    Abstract This research proposes a simulated annealing (SA) approach to minimize makespan for a single Batch-Processing machine. Each job has a corresponding Processing time and size. The machine can process the jobs in Batches as long as the machine capacity is not exceeded. The Processing time of a Batch is equal to the longest Processing time among all jobs in the Batch. Random instances were generated to test our approach with respect to solution quality and run time. The results of the SA approach were compared to CPLEX. Our approach outperforms CPLEX on all the instances.