In this paper, for the first time the cross-docking concept is considered in a vendor-managed inventory (VMI)-based supply chain. In this supply chain, and based on the economic order quantity (EOQ) model, a vendor pr...
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In this paper, for the first time the cross-docking concept is considered in a vendor-managed inventory (VMI)-based supply chain. In this supply chain, and based on the economic order quantity (EOQ) model, a vendor prepares and sends several products to retailers. Then, retailers, based upon customers' order, send products to the cross-dock to be delivered to the customers. Demands of retailers and customers are deterministic and shortage is acceptable as backorder. Presented mathematical model (of integernonlinearprogramming type) seeks to minimize the total cost of the supply chain. Thus, a meta-heuristic algorithm (GA) is used to solve the model. In addition, a number of sample problems are analyzed to evaluate the performance of the solving algorithm. Finally, after the conclusion, some suggestions are provided for future researches.
In this paper, a new method named as the gradually descent method was proposed to solve the discrete global optimization problem. With the aid of an auxiliary function, this method enables to convert the problem of fi...
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In this paper, a new method named as the gradually descent method was proposed to solve the discrete global optimization problem. With the aid of an auxiliary function, this method enables to convert the problem of finding one discrete minimizer of the objective function f to that of finding another at each cycle. The auxiliary function can ensure that a point, except a prescribed point, is not its integer stationary point if the value of objective function at the point is greater than the scalar which is chosen properly. This property leads to a better minimizer of f found more easily by some classical local search methods. The computational results show that this algorithm is quite efficient and reliable for solving nonlinear integer programming problems.
Concave resource allocation problem is an integerprogramming problem of minimizing a nonincreasing concave function subject to a convex nondecreasing constraint and bounded integer variables. This class of problems a...
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Concave resource allocation problem is an integerprogramming problem of minimizing a nonincreasing concave function subject to a convex nondecreasing constraint and bounded integer variables. This class of problems are encountered in optimization models involving economies of scale. In this paper, a new hybrid dynamic programming method was proposed for solving concave resource allocation problems. A convex underestimating function was used to approximate the objective function and the resulting convex subproblem was solved with dynamic programming technique after transforming it into a 0-1 linear knapsack problem. To ensure the convergence, monotonicity and domain cut technique was employed to remove certain integer boxes and partition the revised domain into a union of integer boxes. Computational results were given to show the efficiency of the algorithm.
The location-inventory problem for the supply chain of a product family plays an extremely important role in mass customization. The objective of this paper is to determine the locations of manufacturers and distribut...
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The location-inventory problem for the supply chain of a product family plays an extremely important role in mass customization. The objective of this paper is to determine the locations of manufacturers and distribution centers(DCs), the assignment of each DC to a manufacturer and that of each retailer to a DC, and inventory policy with the aim of simultaneously minimizing the sum of construction, transportation and inventory costs. The location-inventory problem is formulated as a nonlinear integer programming model, for which a heuristic algorithm is derived based on the Lagrangian relaxation approach. The algorithm is implemented using Matlab and Mosek, and numerical experiments show that the proposed heuristic is effective.
In cloud computing, Infrastructure-as-a-Service (IaaS) cloud providers can offer two types of purchasing plans for cloud users, including on-demand plan and reservation plan. Generally reservation price is cheaper tha...
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ISBN:
(纸本)9781479935130
In cloud computing, Infrastructure-as-a-Service (IaaS) cloud providers can offer two types of purchasing plans for cloud users, including on-demand plan and reservation plan. Generally reservation price is cheaper than on-demand price, while reservation plan may cause highly underutilized capacity problem. How to joint optimize the service cost and the resource utilization for clouds is a critical issue. To address this issue, a novel steady broker federation is developed to coordinate service demands in this paper. And the optimal reservation problem can be formulated as a nonlinear integer programming model. Then a fine-grained heuristic algorithm is proposed to reduce its computational complexity and obtain quasi-optimal solutions. Numerical simulations driven by large-scale Parallel Workloads Archive demonstrate that the proposed approach can save considerable costs for cloud users and improves the resource utilization for IaaS cloud providers.
The traditional assignment problem assumes that the number of persons is equal to that of the tasks, beyond that, one person is allowed to undertake only one task and one task must be accomplished by
ISBN:
(纸本)9781467389808
The traditional assignment problem assumes that the number of persons is equal to that of the tasks, beyond that, one person is allowed to undertake only one task and one task must be accomplished by
Systems of nonlinear equations of the form [formula omitted], where A is an m × n matrix of ratmnal constants and [formula omitted] are column vectors, are considered Each [formula omitted] is of the form [formul...
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