In the layout problem of manufacturing cells, rectangular cells are to be positioned without overlapping. The objective is to minimize the total transportation cost, i.e. the sum of distances of all pairs of cells wei...
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In the layout problem of manufacturing cells, rectangular cells are to be positioned without overlapping. The objective is to minimize the total transportation cost, i.e. the sum of distances of all pairs of cells weighted by their flow values. The types of layouts are categorized according to the shape of the transportation system's track. In the case of a closed loop layout, the track has a rectangular shape. A common difficulty of all layout problems is the manner in which distances are measured. A frequently used approximation is the Manhattan distance. However, it is significantly shorter than the exact distance in many cases. Both the metaheuristics and exact models suggested by earlier studies use the Manhattan distance. In this paper, a new mathematical model is suggested for the closed loop layout with exact distances. Many feasible solutions are generated for benchmark problems that are competitive with the solutions provided by metaheuristics.
Motivation: Combinatorial therapies play increasingly important roles in combating complex diseases. Owing to the huge cost associated with experimental methods in identifying optimal drug combinations, computational ...
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Motivation: Combinatorial therapies play increasingly important roles in combating complex diseases. Owing to the huge cost associated with experimental methods in identifying optimal drug combinations, computational approaches can provide a guide to limit the search space and reduce cost. However, few computational approaches have been developed for this purpose, and thus there is a great need of new algorithms for drug combination prediction. Results: Here we proposed to formulate the optimal combinatorial therapy problem into two complementary mathematical algorithms, Balanced Target Set Cover (BTSC) and Minimum Off-Target Set Cover (MOTSC). Given a disease gene set, BTSC seeks a balanced solution that maximizes the coverage on the disease genes and minimizes the off-target hits at the same time. MOTSC seeks a full coverage on the disease gene set while minimizing the off-target set. Through simulation, both BTSC and MOTSC demonstrated a much faster running time over exhaustive search with the same accuracy. When applied to real disease gene sets, our algorithms not only identified known drug combinations, but also predicted novel drug combinations that are worth further testing. In addition, we developed a web-based tool to allow users to iteratively search for optimal drug combinations given a user-defined gene set.
The Quadratic Assignment Problem (QAP) can be solved by linearization, where one formulates the QAP as a mixed integer linear programming (MILP) problem. On the one hand, most of these linearizations are tight, but ra...
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The Quadratic Assignment Problem (QAP) can be solved by linearization, where one formulates the QAP as a mixed integer linear programming (MILP) problem. On the one hand, most of these linearizations are tight, but rarely exploited within a reasonable computing time because of their size. On the other hand, Kaufman and Broeckx formulation (Eur. J. Oper. Res. 2(3):204-211, 1978) is the smallest of these linearizations, but very weak. In this paper, we analyze how the Kaufman and Broeckx formulation can be tightened to obtain better QAP-MILP formulations. As shown in our numerical experiments, these tightened formulations remain small but computationally effective to solve the QAP by means of general purpose MILP solvers.
This paper deals with the Event Scheduling Problem with Consumption and Production of Resources (ESPCPR). ESPCPR is an extension of the Resource Constrained Project Scheduling Problem (RCPSP), where activities requiri...
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In this paper we will prove that rather tight upper bounds can be given for the number of non-unique assignments that are achieved after solving the linearprogramming relaxation of some types of mixedintegerlinear ...
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In this paper we will prove that rather tight upper bounds can be given for the number of non-unique assignments that are achieved after solving the linearprogramming relaxation of some types of mixedintegerlinear assignment problems. Since in these cases the number of splitted assignments is small a heuristic can be used to reach a practically good and feasible assignment. Moreover the type of proof can be exploited for related problems to investigate whether a linearprogramming relaxation will yield mainly integer assignments.
The design and operation of energy systems are key issues for matching energy supply and demand. A systematic procedure, including process design and energy integration techniques for sizing and operation optimization...
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The design and operation of energy systems are key issues for matching energy supply and demand. A systematic procedure, including process design and energy integration techniques for sizing and operation optimization of poly-generation technologies is presented in this paper. The integration of biomass resources as well as a simultaneous multi-objective and multi-period optimization, are the novelty of this work. Considering all these concepts in an optimization model makes it difficult to solve. The decomposition approach is used to deal with this complexity. Several options for integrating biomass in the energy system, namely back pressure steam turbines, biomass rankine cycles (BRC), biomass integrated gasification gas engines (BIGGE), biomass integrated gasification gas turbines, production of synthetic natural gas (SNG) and biomass integrated gasification combined cycles (BIGCC), are considered in this paper. The goal is to simultaneously minimize costs and CO2 emission using multi-objective evolutionary algorithms (EMOO) and mixed integer linear programming (MILP). Finally the proposed model is demonstrated by means of a case study. The results show that the simultaneous production of electricity and heat with biomass and natural gas are reliable upon the established assumptions. Furthermore, higher primary energy savings and CO2 emission reduction, 40%, are obtained through the gradual increase of renewable energy sources as opposed to natural gas usage. However, higher economic profitability, 52%, is achieved with natural gas-based technologies. (C) 2011 Elsevier Ltd. All rights reserved.
Phasor measurement units (PMUs) provide synchronized measurements of voltage and current phasors and can make state estimation more accurate. The objective of optimal PMU placement (OPP) problem is to minimize the num...
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ISBN:
(纸本)9781538626993
Phasor measurement units (PMUs) provide synchronized measurements of voltage and current phasors and can make state estimation more accurate. The objective of optimal PMU placement (OPP) problem is to minimize the number of PMUs required for the system to be completely observable. This paper presents two different formulations of optimal PMU placement (OPP) problem: mixed integer linear programming (MILP) and nonlinearprogramming (NLP). For each formulation, modeling of power flow measurements, zero injection, limited communication facility, and single PMU failure is studied. The contribution of our paper is to conduct a comparison between the MILP and NLP formulations and show the advantages and disadvantages of each formulation.
This paper deals with the Event Scheduling Problem with Consumption and Production of Resources (ESPCPR). ESPCPR is an extension of the Resource Constrained Project Scheduling Problem (RCPSP), where activities requiri...
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This paper deals with the Event Scheduling Problem with Consumption and Production of Resources (ESPCPR). ESPCPR is an extension of the Resource Constrained Project Scheduling Problem (RCPSP), where activities requiring renewable resources arc replaced by events consuming or producing non-renewable resources, the precedence constraints are generalized to define minimal and maximal delays between events and the objective remains the minimization of the makespan. Inspired by previous works on RCPSP, We propose four mixed integer linear programming (MILP) models to solve this problem. Computational results are reported to compare these formulations. (C) 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
Recent trends in process engineering have placed increased emphasis on the design of inherently clean and efficient processes. For example, a wide range of pinch analysis and mathematical programming methods have been...
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Recent trends in process engineering have placed increased emphasis on the design of inherently clean and efficient processes. For example, a wide range of pinch analysis and mathematical programming methods have been developed for designing schemes for water reuse/recycle in industrial plants for both grassroot design and plant retrofit. In the latter case, the conventional approach is to maximize water recovery and thereby minimize fresh water demand and effluent volume. However, it is possible that with such an approach the reductions in environmental impact brought about by saving water can be offset by other impacts arising from increased use of energy and materials in the plant after retrofit. This work presents a model for minimizing the total resource consumption impact of a water reuse/recycle network. The total impact is expressed in terms of emergy - a measure of cumulative solar energy inputs into a life cycle system. A simplified model is proposed that focuses on the impact contributions of water, electrical power and material for capital goods. Two case studies illustrate the approach. Results show that the network with the lowest total impact can be found by sacrificing water recovery for savings in energy and material use. (c) 2007 Curtin University of Technology and John Wiley & Sons, Ltd.
This paper proposes a deterministic two-stage mixed integer linear programming(TSMILP)approach to solve the reserve constrained dynamic economic dispatch(DED)problem considering valve-point effect(VPE).In stage one,th...
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This paper proposes a deterministic two-stage mixed integer linear programming(TSMILP)approach to solve the reserve constrained dynamic economic dispatch(DED)problem considering valve-point effect(VPE).In stage one,the nonsmooth cost function and the transmission loss are piecewise linearized and consequently the DED problem is formulated as a mixed integer linear programming(MILP)problem,which can be solved by commercial *** stage two,based on the solution obtained in stage one,a range compression technique is proposed to make a further exploitation in the subspace of the whole solution *** to the linear approximation of the transmission loss,the solution obtained in stage two dose not strictly satisfies the power balance ***,a forward procedure is employed to eliminate the *** simulation results on four test systems show that TSMILP makes satisfactory performances,in comparison with the existing methods.
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