The THTMTP (two-level hierarchical time minimization transportation problem) is an important problem arising in industries. In literature, there are only two approaches with shortcomings to solve the problem. In this ...
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The THTMTP (two-level hierarchical time minimization transportation problem) is an important problem arising in industries. In literature, there are only two approaches with shortcomings to solve the problem. In this paper, the THTMTP is formulated as a mathematical model applicable to the case in which the total available supply at the sources is no less than the total demand at the destinations. A feasible flow-based iterative algorithm named THTMTP-A is proposed to solve the THTMTP by constructing network with lower and upper arc capacities. It is proved that the THTMTP-A algorithm can find the optimal solution to the THTMTP in a polynomial time. The proposed THTMTP-A algorithm has good performance in terms of computer implementation, computational time and required memory for computation, and hence overcomes successfully the shortcomings of the two existing approaches. Computational experiments validate that the THTMTP-A algorithm is an efficient and robust method to solve the THTMTP, and can serve as efficient tool to solve other related optimization problems. (C) 2017 Elsevier Ltd. All rights reserved.
We consider parallel-machine job scheduling problems with precedence constraints. Job processing times are variable and depend on positions of jobs in a schedule. The objective is to minimize the maximum completion ti...
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We consider parallel-machine job scheduling problems with precedence constraints. Job processing times are variable and depend on positions of jobs in a schedule. The objective is to minimize the maximum completion time or the total weighted completion time. We specify certain conditions under which the problem can be solved by scheduling algorithms applied earlier for fixed job processing times.
In this note we give a short and relatively simple algorithmic proof of a theorem of Benczur and Frank on covering a symmetric crossing supermodular function with a minimum number of graph edges. Our proof method also...
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In this note we give a short and relatively simple algorithmic proof of a theorem of Benczur and Frank on covering a symmetric crossing supermodular function with a minimum number of graph edges. Our proof method also implies a deficient form of the theorem. (C) 2017 Elsevier B.V. All rights reserved.
We consider a class of network-design problems with minimum sum of modification and network costs for minimum spanning trees under Hamming distance. By constructing three auxiliary networks, we present a strongly poly...
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We consider a class of network-design problems with minimum sum of modification and network costs for minimum spanning trees under Hamming distance. By constructing three auxiliary networks, we present a strongly polynomial-time algorithm for this problem. The method can be applied to solve many network-design problems. And, we show that a variation model of this problem is NP-hard, even when the underlying network is a tree, by transforming the 0-1 knapsack problem to this model.
In recent years, balanced network optimization problems play an important role in practice, especially in information transmission, industry production and logistics management. In this paper, we consider some logisti...
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In recent years, balanced network optimization problems play an important role in practice, especially in information transmission, industry production and logistics management. In this paper, we consider some logistics optimization problems related to the optimal tree structures in a network. We show that the most optimal subtree problem is NP-hard by transforming the connected dominating set problem into this model. By constructing the network models of the most balanced spanning tree problem with edge set restrictions, and by finding the optimal subtrees in special networks, we present efficient computational methods for solving some logistics problems.
This paper deals with the deterministic single-item procurement planning problem with batch ordering under the buyback contract. We assume a buyback contract with returns of unused products at the end of each period t...
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This paper deals with the deterministic single-item procurement planning problem with batch ordering under the buyback contract. We assume a buyback contract with returns of unused products at the end of each period t...
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This paper deals with the deterministic single-item procurement planning problem with batch ordering under the buyback contract. We assume a buyback contract with returns of unused products at the end of each period to the supplier and we consider a piecewise procurement cost structure composed by a fixed ordering cost, a variable procurement cost and a fixed cost per batch replenished, incurred by the retailer. This problem is studied under various hypotheses : in the first, the acquisition is made in only full batches, in the second, there is no specific assumption on the acquisition quantity, in the third, the procurement must be in only full batches with a possibility of lost sales, and in the fourth, there is just the option of lost sales for the general case. For these four cases, several optimality properties and polynomial time algorithms are proposed. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
This paper addresses the multi-robot 2-cyclic scheduling problem in a no-wait robotic cell where exactly two parts enter and leave the cell during each cycle and multiple robots on a single track are responsible for t...
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This paper addresses the multi-robot 2-cyclic scheduling problem in a no-wait robotic cell where exactly two parts enter and leave the cell during each cycle and multiple robots on a single track are responsible for transporting parts between machines. We develop a polynomial algorithm to find the minimum number of robots for all feasible cycle times. Consequently, the optimal cycle time for any given number of robots can be obtained with the algorithm. The proposed algorithm can be implemented in O(N(7)) time, where N is the number of machines in the considered robotic cell. (C) 2010 Elsevier Ltd. All rights reserved.
We propose a polynomial algorithm for a separable convex optimization problem with linear constraints. We do not make any additional assumptions about the structure of the objective function except for polynomial comp...
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We propose a polynomial algorithm for a separable convex optimization problem with linear constraints. We do not make any additional assumptions about the structure of the objective function except for polynomial computability. That is, the objective function can be non-differentiable. The running time of our algorithm is polynomial in the size of the input consisting of an instance of the problem and the accuracy with which the problem is to be solved. Our algorithm uses an oracle for solving auxiliary systems of linear inequalities. This oracle can be any polynomial algorithm for linear programming.
In parallel-batching machine scheduling, all jobs in a batch start and complete at the same time, and the processing time of the batch is the maximum processing time of any job in it. For the unbounded parallel-batchi...
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In parallel-batching machine scheduling, all jobs in a batch start and complete at the same time, and the processing time of the batch is the maximum processing time of any job in it. For the unbounded parallel-batching machine scheduling problem of minimizing the maximum lateness, denoted 1|p-batch|L_(max), a dynamic programming algorithm with time complexity O(n^2) is well known in the ***, this algorithm is improved to be an O(n log n) algorithm. In this note, we present another O(n log n) algorithm with simplifications on data structure and implementation details.
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