In recent years, dramatic changes in business factors have triggered a trend of manufacturing relocation out of "The World's Factory", which is the Pearl River Delta (PRD), China. Global manufacturers in...
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ISBN:
(纸本)9781424441358
In recent years, dramatic changes in business factors have triggered a trend of manufacturing relocation out of "The World's Factory", which is the Pearl River Delta (PRD), China. Global manufacturers in PRD have been facing unprecedented operating cost pressure, due to RMB currency appreciation, rising labor cost, highly volatile oil price, tax rebate adjustment and industry policy changes. This paper presents a mixed integer programming (MIP) model, to evaluate the impact of business factors on global manufacturing relocation decisions. Objective function of the MW model is to minimize Total Landed Cost (TLC) for international markets. Application of the MW model is illustrated through a case study with a hypothetical footwear manufacturer. Managerial implications on supply chain dynamics and regional economy are derived from modeling results and analysis.
mixed integer programming (MIP) is a powerful abstraction in combinatorial optimization that finds real-life application across many significant sectors. The recent proliferation of graphical processing unit (GPU)-bas...
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ISBN:
(纸本)9781450384414
mixed integer programming (MIP) is a powerful abstraction in combinatorial optimization that finds real-life application across many significant sectors. The recent proliferation of graphical processing unit (GPU)-based accelerated computing architectures in large-scale parallel computing or supercomputing presents new opportunities as well as challenges in the advancement of MIP solver technology to effectively use the new accelerated computing platforms and scale to large parallel systems. Here, we recount the conventional processor-based strategies and focus on configurations where the most promising intersection lies between parallel MIP solver approaches and the specific strengths of accelerated parallel platforms. We note that the best potential lies in solving problems whose individual matrix sizes (of the linear program relaxation) fit entirely within one accelerator's memory and whose branch-and-bound (or branch-and-cut) trees cannot be fully contained within a small number of computational nodes. Additionally, we identify ideal features of computational linear algebra support on GPU accelerators that would help advance this direction of scalable parallel solution of MIP problems on GPU-based accelerated computing architectures.
We show that the optimal design of non-randomized discrete sequential tests, i.e., tests whose test statistics take on only a countable number of states, can be modeled as a mixedinteger linear problem. This is done ...
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ISBN:
(纸本)9781479928934
We show that the optimal design of non-randomized discrete sequential tests, i.e., tests whose test statistics take on only a countable number of states, can be modeled as a mixedinteger linear problem. This is done by reformulating the difference equations describing the random walk on the integer lattice in terms of linear mixedinteger constraints. We outline the general procedure and give a simple example to show how the proposed method can be used in practice.
We propose modulation codes of 2/3 code rates for multi-level holographic data storage using mixed integer programming approach. In this paper, the signal intensities that are passed through the 4-level holographic ch...
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ISBN:
(纸本)9781467324939;9781467324922
We propose modulation codes of 2/3 code rates for multi-level holographic data storage using mixed integer programming approach. In this paper, the signal intensities that are passed through the 4-level holographic channel are assumed as a four Gaussian mixture. Codeword selection problem with minimal symbol value difference between neighboring cells and near uniform symbol occurrence is formulated as a linear mixed integer programming problem and solved using IBM ILOG CPLEX ver.12.2.
This study proposes a model predictive control framework using a mixed integer programming for the deep neural network (DNN) model with rectified linear unit (ReLU). The accurate DNN model with ReLU using the past inp...
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This study proposes a model predictive control framework using a mixed integer programming for the deep neural network (DNN) model with rectified linear unit (ReLU). The accurate DNN model with ReLU using the past input time series for the diesel engine is constructed. In this method, the ReLU is represented by inequalities including 0-1 variables (binaries). The model predictive control problem is formulated as a mixed integer programming problem and is applied to the control problem of the diesel engine. Dynamical DNN model of a diesel engine is constructed using the experimental data. This model can represent complicate engine phenomena such as strong nonlinearity and delay. Simulation results of the worldwide harmonized transient cycle (WHTC) verify the effectiveness of the proposed method. The difficulties of non-linearity, delay, and interference in the control problem of the diesel engine are solved by using a systematic model predictive control of the DNN model. Copyright (C) 2024 The Authors.
Operational readiness and mission availability are two important standards in equipment supportability. To evaluate these two standards, an improved particle swarm optimization (PSO) algorithm to solve the mixed integ...
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ISBN:
(纸本)9781479986460
Operational readiness and mission availability are two important standards in equipment supportability. To evaluate these two standards, an improved particle swarm optimization (PSO) algorithm to solve the mixed integer programming (MIP) problems has been developed. The augmented Lagrange multiplier method is employed to deal with the constraints, and special update strategy employed to restrict the swarm particles to lies only in integer positions. Tests on the two former mathematical models have verified the effectiveness of the proposed mixed technique, and it can be easily applied to other mixed integer programming with Constraint problem.
This paper proposes an improved differential evolution algorithm, named I-DE, for constrained nonlinear mixed integer programming problems. The new population initialization technology and dynamic non-linear scaling f...
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ISBN:
(纸本)9781479925483
This paper proposes an improved differential evolution algorithm, named I-DE, for constrained nonlinear mixed integer programming problems. The new population initialization technology and dynamic non-linear scaling factor are applied to enhance optimization capability of algorithm. We strengthen influence of constraint matrix to deal with constraint of problems. Introduction of special truncation procedure to handle integer restrictions and selection operator based on Deb constraint rules update the population. The test results show that the I-DE algorithm possess higher success rate and precision than MI-LXPM algorithm and has found solutions which are better than the known optimal solution in five problems.
With the necessity to meet the strict grid regulations, cope with the smart grid trends and improve customer satisfaction, DSOs are required to provide grid expansions and enhancements in a cost-effective manner. A co...
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ISBN:
(纸本)9781728145471
With the necessity to meet the strict grid regulations, cope with the smart grid trends and improve customer satisfaction, DSOs are required to provide grid expansions and enhancements in a cost-effective manner. A common approach to enhance the reliability of supply is for planning engineers to consider ring configurations as an addition to the standard radial feed structure. In this paper, a scenario based mixed integer programming method for ring distribution system expansion planning is proposed. The proposed model extends to consider multiple cable size options for each line corridor and offers the flexibility to select different ring configuration layouts. The proposed model is tested on a realistic 96 bus case study of the Singaporean distribution system. The results of two different test cases with and without considering emergency grid operation are presented and analyzed.
We provide formulation techniques for obtaining sharp (i.e., convex hull) mixed integer programming (MIP) formulations for different classes of lot-sizing problems, including various backlogging models, and with the p...
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Engineer-to-order (ETO) production in which products are designed and manufactured in response to customer orders is required to respond flexibly to customer requests at various stages from design to maintenance. This...
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Engineer-to-order (ETO) production in which products are designed and manufactured in response to customer orders is required to respond flexibly to customer requests at various stages from design to maintenance. This characteristic makes it difficult to apply a standard production planning strategy which divides the planning into three phases, i.e., long-term, medium-term and short-term planning (production scheduling), because there are large discrepancies among the phases and rescheduling requires a lot of man-hours. We proposed a production planning framework that unifies the granularity of resources and unit time in all of the planning phases aiming to reduce the discrepancies, and a model that is commonly used in the three phases of planning was organized as flexible job-shops. This paper provides a mixed integer programming formulation of the production scheduling problem based on the model considering the following characteristics of the target ETO production site: (1) The planner has discretion in shortening required processing time;(2) Operation time is limited to day time of weekdays;(3) Overtime works can be accepted if necessary;(4) Some operations of multiple parts must be processed at the same time on the same machine. A numerical experiment showed validity of the model.
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