Now showing 1 - 10 of 13
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    A performance analysis of dispatching rules and a heuristic in static flowshops with missing operations of jobs
    (16-06-2001) ;
    Ziegler, Hans
    An experimental investigation of the performance of dispatching rules and a heuristic for scheduling in static flowshops with missing operations is undertaken in this study. The measure of performance is the minimization of total flow time of jobs. Permutation schedules are generated by using the heuristic for scheduling. General schedules, which can be permutation or non-permutation schedules, are obtained by using dispatching rules. Four dispatching rules, including a new dispatching rule, are considered. Two types of flowshops are studied: one with no missing operations of jobs and another with missing operations of jobs. In the latter type of flowshops, jobs with varying number of missing operations are considered. An extensive investigation of the performance of the dispatching rules and the heuristic is carried out. It is observed that the heuristic minimizes total flow time of jobs more than dispatching rules up to a certain level of missing operations of jobs in flowshops, after which dispatching rules perform better. The performance of the heuristic and the dispatching rules in terms of minimizing the makespan as a secondary measure is also reported. © 2001 Elsevier Science B.V.
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    Scheduling to minimize the sum of weighted flowtime and weighted tardiness of jobs in a flowshop with sequence-dependent setup times
    (16-09-2003) ;
    Ziegler, Hans
    Efficient heuristics for scheduling jobs in a static flowshop with sequence-dependent setup times of jobs are presented in this paper. The objective is to minimize the sum of weighted flowtime and weighted tardiness of jobs. Two heuristic preference relations are used to construct a good heuristic permutation sequence of jobs. Thereafter, an improvement scheme is implemented, once and twice, on the heuristic sequence to enhance the quality of the solution. An existing heuristic, a random search procedure and a greedy local search are used as benchmark methods for relatively evaluating the proposed heuristics. An extensive performance analysis has shown that the proposed heuristics are computationally faster and more effective in yielding solutions of better quality than the benchmark procedures. © 2002 Elsevier Science B.V. All rights reserved.
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    Ant-colony algorithms for permutation flowshop scheduling to minimize makespan/total flowtime of jobs
    (01-06-2004) ;
    Ziegler, Hans
    The problem of scheduling in permutation flowshops is considered with the objective of minimizing the makespan, followed by the consideration of minimization of total flowtime of jobs. Two ant-colony optimization algorithms are proposed and analyzed for solving the permutation flowshop scheduling problem. The first algorithm extends the ideas of the ant-colony algorithm by Stuetzle [Proceedings of the 6th European Congress on Intelligent Techniques and Soft Computing (EUFIT '98), vol. 3, Verlag Mainz, Aachen, Germany, 1998, p. 1560], called max-min ant system (MMAS), by incorporating the summation rule suggested by Merkle and Middendorf [Proceedings of the EvoWorkshops 2000, Lecture Notes in Computer Science No. 1803, Springer-Verlag, Berlin, 2000, p. 287] and a newly proposed local search technique. The second ant-colony algorithm is newly developed. The proposed ant-colony algorithms have been applied to 90 benchmark problems taken from Taillard [European Journal of Operational Research 64 (1993) 278]. First, a comparison of the solutions yielded by the MMAS and the two ant-colony algorithms developed in this paper, with the heuristic solutions given by Taillard [European Journal of Operational Research 64 (1993) 278] is undertaken with respect to the minimization of makespan. The comparison shows that the two proposed ant-colony algorithms perform better, on an average, than the MMAS. Subsequently, by considering the objective of minimizing the total flowtime of jobs, a comparison of solutions yielded by the proposed ant-colony algorithms with the best heuristic solutions known for the benchmark problems, as published in an extensive study by Liu and Reeves [European Journal of Operational Research 132 (2001) 439], is carried out. The comparison shows that the proposed ant-colony algorithms are clearly superior to the heuristics analyzed by Liu and Reeves. For 83 out of 90 problems considered, better solutions have been found by the two proposed ant-colony algorithms, as compared to the solutions reported by Liu and Reeves. © 2003 Elsevier B.V. All rights reserved.
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    Minimum cost berth allocation problem in maritime logistics: new mixed integer programming models
    (01-06-2019)
    Jos, Bobin Cherian
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    Harimanikandan, M.
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    Ziegler, Hans
    The berth allocation problem (BAP) involves decisions on how to allocate the berth space and to sequence maritime vessels that are to be loaded and unloaded at a container terminal involved in the maritime logistics. As the berth is a critical resource in a container terminal, an effective use of it is highly essential to have efficient berthing and servicing of vessels, and to optimize the associated costs. This study focuses on the minimum cost berth allocation problem (MCBAP) at a container terminal where the maritime vessels arrive dynamically. The objective comprises the waiting time penalty, tardiness penalty, handling cost and benefit of early service completion of vessels. This paper proposes three computationally efficient mixed integer linear programming (MILP) models for the MCBAP. Through numerical experiments, the proposed MILP models are compared to an existing model in the literature to evaluate their computational performance. The computational study with problem instances of various problem characteristics demonstrates the computational efficiency of the proposed models.
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    The value of information sharing in a serial supply chain with AR(1) demand and non-zero replenishment lead times
    (01-12-2016)
    Sabitha, Devarajulu
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    Kalpakam, S.
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    Ziegler, Hans
    This paper analyzes the value of information sharing, in terms of reduction in the demand variance and average (on-hand) inventory level, in a single product multi-stage (i.e., serial) supply chain with non-zero replenishment lead times. An order-one auto-regressive, AR(1), process characterizes the customer demand. We quantify the reduction in the demand variance and average (on-hand) inventory level in a multi-stage supply chain considering two information sharing scenarios: (1) supply-chain-wide information sharing; and (2) Vendor-Managed Inventory (VMI). In contrast to the related existing literature on a three-stage supply chain with non-zero replenishment lead times, we prove for a multi-stage supply chain that there exists no difference, in terms of the expectation and the variance of total demand over lead time, between supply-chain-wide information sharing and VMI. When there is an instantaneous replenishment across all firms, our analytical results are in agreement with the existing literature on a multi-stage supply chain. Further, we show that the value of information sharing is always greater than or equal to those obtained by an existing study. We also observe that the variance of total demand over lead time is reflected in the variance of the inventory level, derived using inventory balance equation. Furthermore, we carry out a comparative study with respect to the benefits of information sharing under three different supply chain settings, and find that the value of information sharing is more for upstream firms, when demand correlation over a period is high or when lead times are high or both.
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    Heuristics for scheduling in a flowshop with setup, processing and removal times separated
    (01-01-1997) ;
    Ziegler, Hans
    The problem of scheduling in a flowshop, where setup, processing and removal times are separable, is considered with the objective of minimizing makespan. Heuristic algorithms are developed by the introduction of simplifying assumptions into the scheduling problem under study. An improvement method is incorporated in the heuristics to enhance the quality of their solutions. The proposed heuristics and an existing heuristic are evaluated by a large number of randomly generated problems. The results of an extensive computational investigation for various values of parameters are presented. © 1997 Taylor & Francis Ltd.
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    An ant colony algorithm for scheduling in flowshops with sequence-dependent setup times of jobs
    (01-09-2006)
    Gajpal, Yuvraj
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    Ziegler, Hans
    The problem of scheduling in flowshops with sequence-dependent setup times of jobs is considered and solved by making use of ant colony optimization (ACO) algorithms. ACO is an algorithmic approach, inspired by the foraging behavior of real ants, that can be applied to the solution of combinatorial optimization problems. A new ant colony algorithm has been developed in this paper to solve the flowshop scheduling problem with the consideration of sequence-dependent setup times of jobs. The objective is to minimize the makespan. Artificial ants are used to construct solutions for flowshop scheduling problems, and the solutions are subsequently improved by a local search procedure. An existing ant colony algorithm and the proposed ant colony algorithm were compared with two existing heuristics. It was found after extensive computational investigation that the proposed ant colony algorithm gives promising and better results, as compared to those solutions given by the existing ant colony algorithm and the existing heuristics, for the flowshop scheduling problem under study.
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    Two ant-colony algorithms for minimizing total flowtime in permutation flowshops
    (01-06-2005) ;
    Ziegler, Hans
    The problem of scheduling in flowshops with the objective of minimizing total flowtime is studied. For solving the problem two ant-colony algorithms are proposed and analyzed. The first algorithm refers to some extent to ideas by Stuetzle [Stuetzle, T. (1998). An ant approach for the flow shop problem. In: Proceedings of the sixth European Congress on intelligent techniques and soft computing (EUFIT '98) (Vol. 3) (pp. 1560-1564). Aachen: Verlag Mainz] and Merkle and Middendorf [Merkle, D., & Middendorf, M. (2000). An ant algorithm with a new pheromone evaluation rule for total tardiness problems. In: Proceedings of the EvoWorkshops 2000, lecture notes in computer science 1803 (pp. 287-296). Berlin: Springer]. The second algorithm is newly developed. The proposed ant-colony algorithms have been applied to 90 benchmark problems taken from Taillard [Taillard, E. (1993). Benchmarks for basic scheduling problems. European Journal of Operational Research, 64, 278-285]. A comparison of the solutions yielded by the ant-colony algorithms with the best heuristic solutions known for the benchmark problems up to now, as published in extensive studies by Liu and Reeves [Liu, J., & Reeves, C.R. (2001). Constructive and composite heuristic solutions to the P//ΣCi scheduling problem. European Journal of Operational Research, 132, 439-452, and Rajendran and Ziegler [Rajendran, C., & Ziegler, H. (2004). Ant-colony algorithms for permutation flowshop scheduling to minimize makespan/total flowtime of jobs. European Journal of Operational Research, 155, 426-438], shows that the presented ant-colony algorithms are better, on an average, than the heuristics analyzed by Liu and Reeves and Rajendran and Ziegler. © 2004 Elsevier Ltd. All rights reserved.
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    Capacitated lot-sizing problem with production carry-over and set-up splitting: Mathematical models
    (17-04-2016)
    Ramya, Ravi
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    Ziegler, Hans
    This work proposes mathematical models (MMs) for the capacitated lot-sizing problem with production carry-over and set-up splitting, which can handle two scenarios, namely (1) situation/scenario where the set-up costs and holding costs are product dependent and time independent, and with no backorders or lost sales, and (2) situation where the set-up costs and holding costs are product dependent and time dependent, and with no backorders or lost sales. Previously, in an existing study the authors had developed a MM for the same problem and situation where the set-up costs and holding costs are product dependent and time independent, i.e. our Scenario 1. We compare our proposed models with the model in the existing study that appears to be incorrect.
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    Priority fractional rationing (PFR) policy and a hybrid metaheuristic for managing stock in divergent supply chains
    (01-12-2022)
    John, Kurian
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    Paul, Brijesh
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    Ziegler, Hans
    A distributor catering to demands of multiple retailers is considered in this paper and stock-management in this divergent supply chain is achieved through the deployment of periodic review base-stock (i.e. (R, S) policy) policy at every member. In the model of the supply chain considered in this study, in every time-period, an attempt is made by the distributor to first transport backlogged-demands from the downstream members till the distributor’s previous instance-of-review even before considering demands from downstream members in recent time-periods. This practice of the distributor attempting first to satisfy backlogged-demands till its last instance of review will ensure that the shipment will reach the retailer, contemplating whom the order was made by the distributor. A Mixed Integer Linear Programming (MILP)-based mathematical formulation of the supply chain (with the objective of minimizing the Total Supply Chain Cost (TSCC)), to obtain optimum policy (R, S) parameters at each member of the supply chain, and inherently performing the allocation and rationing of stock over a finite planning horizon, is proposed through this paper. A new heuristic allocation and rationing mechanism for the distributor to distribute stock among retailers during the occurrence of shortage named as Priority Fractional Rationing (PFR) policy is also introduced in this study. A heuristic methodology which is a hybrid of Genetic Algorithm and Particle Swarm Optimization algorithm (HGA-PSO) combined with PFR policy is proposed through this study after analyzing the computational difficulty encountered and lack of tractability of stock-allocation and stock-rationing mechanism while the MILP-based mathematical formulation is solved to optimality. A local search technique as part of the Particle Swarm Optimization (PSO) algorithm, similar to mutation operation in Genetic Algorithm (GA) is introduced due to the observation of inferior results during pilot studies. The performance evaluation studies of the HGA-PSO with that of stand-alone GA, stand-alone PSO with new local search and the exact solution obtained by solving the MILP-based mathematical formulation is presented. The results indicate the superior performance of the hybrid algorithm in comparison with stand-alone GA and PSO.