Irregular low-density parity-check (LDPC) code design for parallel sub-channels with different qualities is investigated. Such channels appear in many communication systems, e. g., orthogonal frequency-division multip...
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Irregular low-density parity-check (LDPC) code design for parallel sub-channels with different qualities is investigated. Such channels appear in many communication systems, e. g., orthogonal frequency-division multiplexing systems. When channel knowledge is available at both the transmitter and receiver, following the literature, we consider allotted LDPC codes which carefully assign different parts of the code to sub-channels. To reduce the number of design parameters and allow for efficient design, semi-regular allotted codes have been suggested. We first formulate the design of semi-regular codes as a mixedinteger linear programming. Relaxing the semi-regularity constraint broadens the search space which results in improved codes and also a more efficient design via linear programming. While information theoretic results suggest that having channel state information-for a fixed power assignment-does not change the capacity, we show that under non-optimal decoding or when the maximum degree allowed in the code is small, allotted codes significantly outperform conventional ones. Finally, for the case that neither side has the channel knowledge (thus capacity-loss is inevitable), we see that the reduced capacity can still be approached by LDPC codes.
An efficient systematic iterative solution strategy for solving real-world scheduling problems in multi-product multistage batch plants is presented. Since the proposed method has its core a mathematical model, two al...
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An efficient systematic iterative solution strategy for solving real-world scheduling problems in multi-product multistage batch plants is presented. Since the proposed method has its core a mathematical model, two alternative MIP scheduling formulations are suggested. The MIP-based solution strategy consists of a constructive step, wherein a feasible and initial solution is rapidly generated by following an iterative insertion procedure, and an improvement step, wherein the initial solution is systematically enhanced by implementing iteratively several rescheduling techniques, based on the mathematical model. A salient feature of our approach is that the scheduler can maintain the number of decisions at a reasonable level thus reducing appropriately the search space. A fact that usually results in manageable model sizes that often guarantees a more stable and predictable optimization model behavior. The proposed strategy performance is tested on several complicated problem instances of a multiproduct multistage pharmaceuticals scheduling problem. On average, high quality solutions are reported with relatively low computational effort. Authors encourage other researchers to adopt the large-scale pharmaceutical scheduling problem to test on it their solution techniques, and use it as a challenging comparison reference. (C) 2010 Elsevier By. All rights reserved.
In this paper, we address the following probabilistic version (PSC) of the set covering problem: min{cx vertical bar P(Ax >= xi) >= p, x is an element of {0, 1}(N)} where A is a 0-1 matrix, xi is a random 0-1 ve...
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In this paper, we address the following probabilistic version (PSC) of the set covering problem: min{cx vertical bar P(Ax >= xi) >= p, x is an element of {0, 1}(N)} where A is a 0-1 matrix, xi is a random 0-1 vector and p is an element of (0, 1] is the threshold probability level. We introduce the concepts of p-inefficiency and polarity cuts. While the former is aimed at deriving an equivalent MIP reformulation of (PSC), the latter is used as a strengthening device to obtain a stronger formulation. Simplifications of the MIP model which result when one of the following conditions hold are briefly discussed: A is a balanced matrix, A has the circular ones property, the components of xi are pairwise independent, the distribution function of xi is a stationary distribution or has the disjunctive shattering property. We corroborate our theoretical findings by an extensive computational experiment on a test-bed consisting of almost 10,000 probabilistic instances. This test-bed was created using deterministic instances from the literature and consists of probabilistic variants of the set covering model and capacitated versions of facility location, warehouse location and k-median models. Our computational results show that our procedure is orders of magnitude faster than any of the existing approaches to solve (PSC), and in many cases can reduce hours of computing time to a fraction of a second.
In this study, we introduce simultaneous effects of learning and linear deterioration into assembly line balancing problem. In many realistic settings. although the actual task time of a task is modeled as an increasi...
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In this study, we introduce simultaneous effects of learning and linear deterioration into assembly line balancing problem. In many realistic settings. although the actual task time of a task is modeled as an increasing function of its starting time due to deterioration effects the produced worker(s) (or machine(s)) develops continuously by repeated the same or similar activities The objective of problem is to minimize the station number For this purpose, a mixed nonlinear integerprogramming model is developed. This paper also discusses the adaptation of the COMSOAL approach for large scale assembly line balancing problem with deterioration task and learning effect. (C) 2009 Elsevier Ltd All rights reserved
A mixed integer programming formulation is proposed for hub-and-spoke network design in a competitive environment. It addresses the competition between a newcomer liner service provider and an existing dominating oper...
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A mixed integer programming formulation is proposed for hub-and-spoke network design in a competitive environment. It addresses the competition between a newcomer liner service provider and an existing dominating operator, both operating on hub-and-spoke networks. The newcomer company maximizes its market share which depends on the service time and transportation cost by locating a predefined number of hubs at candidate ports and designing its network. While general-purpose solvers do not solve instances of even small size, an accelerated Lagrangian method combined with a primal heuristic obtains promising bounds. Our computational experiments on real instances of practical size indicate superiority of our approach. (C) 2010 Elsevier Ltd. All rights reserved.
We consider consistent tests for stochastic dominance efficiency at any order of a given portfolio with respect to all possible portfolios constructed from a set of assets. We justify block bootstrap approaches to ach...
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We consider consistent tests for stochastic dominance efficiency at any order of a given portfolio with respect to all possible portfolios constructed from a set of assets. We justify block bootstrap approaches to achieve valid inference in a time series setting. The test statistics are computed using linear and mixed integer programming formulations. Monte Carlo results show that the bootstrap procedure performs well in finite samples. The empirical application reveals that the Fama and French market portfolio is first and second-order stochastic dominance efficient, although it is mean-variance inefficient.
This article deals with the ring star problem. It consists of finding a ring that goes through a central node and assigning every node not in the ring to a node in the ring so that the total design and assignment cost...
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This article deals with the ring star problem. It consists of finding a ring that goes through a central node and assigning every node not in the ring to a node in the ring so that the total design and assignment cost is minimized. We propose a new formulation based on the so-called st-chains which represent simple paths between two specific nodes s and t. We introduce new facet-defining inequalities and we develop an efficient branch-and-cut algorithm for the problem. Computational results that show the efficiency of our approach are presented.
In the last few years, several different mesh network architectures have been conceived by both industry and academia;however, many issues on the deployment of efficient and fair transport protocols are still open. On...
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In the last few years, several different mesh network architectures have been conceived by both industry and academia;however, many issues on the deployment of efficient and fair transport protocols are still open. One of these issues is rate adaptation, that is, how to allocate the network resources among multiple flows, while minimizing the performance overhead. In order to address this problem, in this paper, we first define an analytical framework for a very simple topology. The model allows us to study the performance of an adaptive and responsive transport protocol when the effect of the lower layers are ignored. The mathematical approach alone does not represent a feasible solution, but it contributes to determining the strengths and weaknesses of our proposal. The main novelty of the proposed solution is that the congestion control approach is based on a hop-by-hop mechanism, which allows nodes to adapt their transmitting rates in a distributed way and to keep track of dynamic multi-hop network characteristics in a responsive manner. This is in contrast with classical literature solutions, founded on an end-to-end support. Anyway, to ensure the reliability, a coarse-grained end-to-end algorithm is integrated with the proposed hop-by-hop congestion control mechanism to provide packet level reliability at the transport layer. Performance evaluation, via extensive simulation experiments, shows that the proposed protocol achieves a high performance in terms of network throughput. (C) 2010 Elsevier Inc. All rights reserved.
This paper is concerned with model development for a short-term fleet deployment problem of liner shipping operations. We first present a mixedinteger nonlinear programming model in which the optimal vessel speeds fo...
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This paper is concerned with model development for a short-term fleet deployment problem of liner shipping operations. We first present a mixedinteger nonlinear programming model in which the optimal vessel speeds for different vessel types on different routes are interpreted as their realistic optimal travel times. We then linearize the proposed nonlinear model and obtain a mixedinteger linear programming (MILP) model that can be efficiently solved by a standard mixed integer programming solver such as CPLEX The MILP model determines the optimal route service frequency pattern and take into account the time window constraints of shipping services. Finally, we report our numerical results and performance of CPLEX on randomly generated instances. (C) 2009 Elsevier Ltd. All rights reserved.
The production planning of regional small-scale soft drink plants can be modeled by mixedinteger models that integrate lot sizing and scheduling decisions and consider sequence-dependent setup times and costs. These ...
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The production planning of regional small-scale soft drink plants can be modeled by mixedinteger models that integrate lot sizing and scheduling decisions and consider sequence-dependent setup times and costs. These plants produce soft drinks in different flavors and sizes and they have typically only one production line. The production process is carried out basically in two main stages: liquid preparation (stage I) and bottling (stage II). However, since the production bottleneck of these plants is often in stage II, in this study we represent the problem as a one-stage one-machine lot-scheduling model that considers stage II as the bottleneck but also takes into account a capacity constraint of stage I. To solve the problem, we propose relax and fix heuristics exploring the model structure and we evaluate their computational performances solving different problem instances based on real data of a Brazilian small-scale soft drink company. The solutions obtained are compared to the company solutions and the solutions of a general-purpose optimization software. (C) 2009 Elsevier Ltd. All rights reserved.
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