The Experts below are selected from a list of 166287 Experts worldwide ranked by ideXlab platform
Gerhard Wascher - One of the best experts on this subject based on the ideXlab platform.
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Order picking with multiple pickers and due dates simultaneous solution of Order batching batch assignment and sequencing and picker routing problems
European Journal of Operational Research, 2017Co-Authors: Andre Scholz, Daniel Schubert, Gerhard WascherAbstract:Abstract In manual picker-to-part Order picking systems, human operators (Order pickers) walk or ride through the warehouse, retrieving items from their storage locations in Order to satisfy a given demand specified by Customer Orders. Each Customer Order is characterized by a certain due date until which all items included in the Order are to be retrieved. For the actual picking process, Customer Orders may be grouped (batched) into more substantial picking Orders (batches). The items of a batch are then collected on a picker tour. Thus, the picking process of each Customer Order in the batch is completed when the picker returns to the depot after the last item of the batch has been picked. Whether and to what extent due dates are violated depends on how the Customer Orders are batched, how the batches are assigned to Order pickers, how the assigned batches are sequenced and how the pickers are routed. Existing literature has only dealt with specific aspects of this problem so far. In this paper, for the first time, an approach is proposed which considers all subproblems simultaneously. A mathematical model of the problem is introduced that allows for solving small problem instances. For larger instances, a variable neighborhood descent algorithm is presented. By means of numerical experiments, it is demonstrated that the algorithm provides solutions of excellent quality. Furthermore, it is shown that a simultaneous solution approach to the above-mentioned subproblems can be considered as a significant source for improving the efficiency of operations in distribution warehouses.
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Order picking with multiple pickers and due dates simultaneous solution of Order batching batch assignment and sequencing and picker routing problems
European Journal of Operational Research, 2017Co-Authors: Andre Scholz, Daniel Schubert, Gerhard WascherAbstract:In manual picker-to-parts Order picking systems of the kind considered in this article, human operators (Order pickers) walk or ride through the warehouse, retrieving items from their storage location in Order to satisfy a given demand specified by Customer Orders. Each Customer Order is characterized by a certain due date until which all requested items included in the Order are to be retrieved and brought to the depot. For the actual picking process, Customer Orders may be grouped (batched) into more substantial picking Orders (batches). The items of a picking Order are then collected on a picker tour through the warehouse. Thus, the picking process of each Customer Order in the batch is only completed when the picker returns to the depot after the last item of the batch has been picked. Whether and to which extend due dates are violated (tardiness) depends on how the Customer Orders are batched, how the batches are assigned to Order pickers, how the assigned batches are sequenced and how the pickers are routed through the warehouse. Existing literature has only treated special aspects of this problem (i.e. the batching problem or the routing problem) so far. In this paper, for the first time, an approach is proposed which considers all aspects simultaneously. A mathematical model of the problem is introduced that allows for solving small problem instances in reasonable computing times. For larger instances, a variable neighborhood descent (VND) algorithm is presented which includes various neighborhood structures regarding the batching and sequencing problem. Furthermore, two sophisticated routing algorithms are integrated into the VND algorithm. By means of numerical experiments, it is shown that this algorithm provides solutions of excellent quality.
Andre Scholz - One of the best experts on this subject based on the ideXlab platform.
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Order picking with multiple pickers and due dates simultaneous solution of Order batching batch assignment and sequencing and picker routing problems
European Journal of Operational Research, 2017Co-Authors: Andre Scholz, Daniel Schubert, Gerhard WascherAbstract:Abstract In manual picker-to-part Order picking systems, human operators (Order pickers) walk or ride through the warehouse, retrieving items from their storage locations in Order to satisfy a given demand specified by Customer Orders. Each Customer Order is characterized by a certain due date until which all items included in the Order are to be retrieved. For the actual picking process, Customer Orders may be grouped (batched) into more substantial picking Orders (batches). The items of a batch are then collected on a picker tour. Thus, the picking process of each Customer Order in the batch is completed when the picker returns to the depot after the last item of the batch has been picked. Whether and to what extent due dates are violated depends on how the Customer Orders are batched, how the batches are assigned to Order pickers, how the assigned batches are sequenced and how the pickers are routed. Existing literature has only dealt with specific aspects of this problem so far. In this paper, for the first time, an approach is proposed which considers all subproblems simultaneously. A mathematical model of the problem is introduced that allows for solving small problem instances. For larger instances, a variable neighborhood descent algorithm is presented. By means of numerical experiments, it is demonstrated that the algorithm provides solutions of excellent quality. Furthermore, it is shown that a simultaneous solution approach to the above-mentioned subproblems can be considered as a significant source for improving the efficiency of operations in distribution warehouses.
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Order picking with multiple pickers and due dates simultaneous solution of Order batching batch assignment and sequencing and picker routing problems
European Journal of Operational Research, 2017Co-Authors: Andre Scholz, Daniel Schubert, Gerhard WascherAbstract:In manual picker-to-parts Order picking systems of the kind considered in this article, human operators (Order pickers) walk or ride through the warehouse, retrieving items from their storage location in Order to satisfy a given demand specified by Customer Orders. Each Customer Order is characterized by a certain due date until which all requested items included in the Order are to be retrieved and brought to the depot. For the actual picking process, Customer Orders may be grouped (batched) into more substantial picking Orders (batches). The items of a picking Order are then collected on a picker tour through the warehouse. Thus, the picking process of each Customer Order in the batch is only completed when the picker returns to the depot after the last item of the batch has been picked. Whether and to which extend due dates are violated (tardiness) depends on how the Customer Orders are batched, how the batches are assigned to Order pickers, how the assigned batches are sequenced and how the pickers are routed through the warehouse. Existing literature has only treated special aspects of this problem (i.e. the batching problem or the routing problem) so far. In this paper, for the first time, an approach is proposed which considers all aspects simultaneously. A mathematical model of the problem is introduced that allows for solving small problem instances in reasonable computing times. For larger instances, a variable neighborhood descent (VND) algorithm is presented which includes various neighborhood structures regarding the batching and sequencing problem. Furthermore, two sophisticated routing algorithms are integrated into the VND algorithm. By means of numerical experiments, it is shown that this algorithm provides solutions of excellent quality.
Daniel Schubert - One of the best experts on this subject based on the ideXlab platform.
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Order picking with multiple pickers and due dates simultaneous solution of Order batching batch assignment and sequencing and picker routing problems
European Journal of Operational Research, 2017Co-Authors: Andre Scholz, Daniel Schubert, Gerhard WascherAbstract:Abstract In manual picker-to-part Order picking systems, human operators (Order pickers) walk or ride through the warehouse, retrieving items from their storage locations in Order to satisfy a given demand specified by Customer Orders. Each Customer Order is characterized by a certain due date until which all items included in the Order are to be retrieved. For the actual picking process, Customer Orders may be grouped (batched) into more substantial picking Orders (batches). The items of a batch are then collected on a picker tour. Thus, the picking process of each Customer Order in the batch is completed when the picker returns to the depot after the last item of the batch has been picked. Whether and to what extent due dates are violated depends on how the Customer Orders are batched, how the batches are assigned to Order pickers, how the assigned batches are sequenced and how the pickers are routed. Existing literature has only dealt with specific aspects of this problem so far. In this paper, for the first time, an approach is proposed which considers all subproblems simultaneously. A mathematical model of the problem is introduced that allows for solving small problem instances. For larger instances, a variable neighborhood descent algorithm is presented. By means of numerical experiments, it is demonstrated that the algorithm provides solutions of excellent quality. Furthermore, it is shown that a simultaneous solution approach to the above-mentioned subproblems can be considered as a significant source for improving the efficiency of operations in distribution warehouses.
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Order picking with multiple pickers and due dates simultaneous solution of Order batching batch assignment and sequencing and picker routing problems
European Journal of Operational Research, 2017Co-Authors: Andre Scholz, Daniel Schubert, Gerhard WascherAbstract:In manual picker-to-parts Order picking systems of the kind considered in this article, human operators (Order pickers) walk or ride through the warehouse, retrieving items from their storage location in Order to satisfy a given demand specified by Customer Orders. Each Customer Order is characterized by a certain due date until which all requested items included in the Order are to be retrieved and brought to the depot. For the actual picking process, Customer Orders may be grouped (batched) into more substantial picking Orders (batches). The items of a picking Order are then collected on a picker tour through the warehouse. Thus, the picking process of each Customer Order in the batch is only completed when the picker returns to the depot after the last item of the batch has been picked. Whether and to which extend due dates are violated (tardiness) depends on how the Customer Orders are batched, how the batches are assigned to Order pickers, how the assigned batches are sequenced and how the pickers are routed through the warehouse. Existing literature has only treated special aspects of this problem (i.e. the batching problem or the routing problem) so far. In this paper, for the first time, an approach is proposed which considers all aspects simultaneously. A mathematical model of the problem is introduced that allows for solving small problem instances in reasonable computing times. For larger instances, a variable neighborhood descent (VND) algorithm is presented which includes various neighborhood structures regarding the batching and sequencing problem. Furthermore, two sophisticated routing algorithms are integrated into the VND algorithm. By means of numerical experiments, it is shown that this algorithm provides solutions of excellent quality.
Teng Miao - One of the best experts on this subject based on the ideXlab platform.
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high frequency information content in end user foreign exchange Order flows
European Journal of Finance, 2012Co-Authors: Ian W Marsh, Teng MiaoAbstract:This article considers the impact of foreign exchange (FX) Order flows on contemporaneous and future stock market returns using a new database of Customer Order flows in the euro-dollar exchange rate market as seen by a leading European bank. We do not find clear contemporaneous relationships between FX Order flows and stock market changes at high frequencies, but FX flows do appear to have significant power to forecast stock index returns over 1–30 min horizons, after controlling for lagged exchange rate and stock market returns. The effects of Order flows from financial Customers on future stock market changes are negative, while the effects of corporate Orders are positive. The latter results are consistent with the premise that corporate Order flows contain dispersed, passively acquired information about fundamentals. Thus, purchases of the dollar by corporate Customers represent good news about the state of the US economy. Importantly, though, there also appears to be extra information in corporate f...
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high frequency information content in end user foreign exchange Order flows
Social Science Research Network, 2010Co-Authors: Ian W Marsh, Teng MiaoAbstract:This paper considers the impact of foreign exchange Order flows on contemporaneous and future stock market returns using a new database of Customer Order flows in the €-$ exchange rate market as seen by a leading European bank. We do not find clear contemporaneous relationships between FX Order flows and stock market changes at high frequencies, but FX flows do appear to have significant power to forecast stock index returns over 1-minute to 30-minute horizons, after controlling for lagged exchange rate and stock market returns. The effects of Order flows from financial Customers on future stock market changes are negative, while the effects of corporate Orders are positive. The latter results are consistent with the premise that corporate Order flows contain dispersed, passively acquired information about fundamentals. Thus purchases of the dollar by corporate Customers represent good news about the state of the US economy. Importantly, though, there also appears to be extra information in corporate flows which is directly relevant to equity prices over and above the impact derived from stock prices reacting to (predicted) exchange rate changes. Interpretation of the financial Customer results is more difficult, although our findings suggest that these flows only affect stock prices through their impact on the value of the dollar.
E G Kyriakidis - One of the best experts on this subject based on the ideXlab platform.
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a single vehicle routing problem with pickups and deliveries continuous random demands and predefined Customer Order
European Journal of Operational Research, 2015Co-Authors: Theodosis D Dimitrakos, E G KyriakidisAbstract:Abstract This paper extends the results of a particular capacitated vehicle routing problem with pickups and deliveries (see Pandelis et al., 2013b) to the case in which the demands for a material that is delivered to N Customers and the demands for a material that is collected from the Customers are continuous random variables instead of discrete ones. The Customers are served according to a particular Order. The optimal policy that serves all Customers has a specific threshold-type structure and it is computed by a suitable efficient dynamic programming algorithm that operates over all policies having this structure. The structural result is illustrated by a numerical example.
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single vehicle routing problems with a predefined Customer Order unified load and stochastic discrete demands
Probability in the Engineering and Informational Sciences, 2013Co-Authors: Dimitrios G Pandelis, Constantinos C Karamatsoukis, E G KyriakidisAbstract:We consider the problem of finding the optimal routing of a single vehicle that delivers K different products to N Customers that are served according to a particular Order. It is assumed that the demands of the Customers for each product are discrete random variables, and the total demand of each Customer for all products cannot exceed the vehicle capacity. The joint probability mass function of the demands of each Customer is known. It is assumed that all products are stored together in the vehicle's single compartment. The policy that serves all Customers with the minimum total expected cost is found by implementing a suitable dynamic programming algorithm. We prove that this policy has a specific threshold-type structure. Furthermore, we study a corresponding infinite-time horizon problem in which the service of the Customers is not completed when the last Customer has been serviced but it continues periodically with the same Customer Order. The demands of each Customer for the products have the same distributions at different periods. The discounted cost optimal policy and the average-cost optimal policy have the same structure as the optimal policy in the finite-horizon problem. Numerical results are given that illustrate the structural results.
