A supervised discriminant mixed integer programming algorithm (DISMIP) is described which achieves either linear or non-linear separation, without assuming any specific probability distribution. This system offers gre...
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A positive relationship between treatment volume and outcome quality has been demonstrated in the literature and is thus evident for a variety of procedures. Consequently, policy makers have tried to translate this so...
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A positive relationship between treatment volume and outcome quality has been demonstrated in the literature and is thus evident for a variety of procedures. Consequently, policy makers have tried to translate this so-called volume-outcome relationship into minimum volume regulation (MVR) to increase the quality of care-yet with limited success. Until today, the effect of strict MVR application remains unclear as outcome quality gains cannot be estimated adequately and restrictions to application such as patient travel time and utilization of remaining hospital capacity are not considered sufficiently. Accordingly, when defining MVR, its effectiveness cannot be assessed. Thus, we developed a mixed integer programming model to define minimum volume thresholds balancing utility in terms of outcome quality gain and feasibility in terms of restricted patient travel time and utilization of hospital capacity. We applied our model to the German hospital sector and to four surgical procedures. Results showed that effective MVR needs a minimum volume threshold of 125 treatments for cholecystectomy, of 45 and 25 treatments for colon and rectum resection, respectively, of 32 treatments for radical prostatectomy and of 60 treatments for total knee arthroplasty. Depending on procedure type and incidence as well as the procedure's complication rate, outcome quality gain ranged between 287 (radical prostatectomy) and 977 (colon resection) avoidable complications (11.7% and 11.9% of all complications). Ultimately, policy makers can use our model to leverage MVR's intended benefit: concentrating treatment delivery to improve the quality of care.
A novel beam orientation optimization algorithm for intensity-modulated radiation therapy (IMRT) was developed. In addition, the effect of candidate pool of beam orientations, in terms of beam orientation resolution a...
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ISBN:
(纸本)9783540368397
A novel beam orientation optimization algorithm for intensity-modulated radiation therapy (IMRT) was developed. In addition, the effect of candidate pool of beam orientations, in terms of beam orientation resolution and the starting orientation, on the optimized beam configuration, plan quality and the optimization time was also explored. The algorithm is based on the technique of mixedinteger linear programming in which binary and positive float variables are employed to represent candidates of beam orientation and beamlet weights, respectively. Both beam orientations and beam intensity maps are simultaneously optimized in the algorithm with a deterministic method. Several clinical cases were used to test the algorithm and the results showed that both target coverage and critical structures sparing were significantly improved for the plans with optimized beam orientations compared to those with equi-spaced beam orientations. The calculation time was less than an hour for the cases with 36 binary variables on a PC with a Pentium IV 2.66 GHz processor. It is also found that decreasing beam orientation resolution to 10 degrees greatly reduced the size of candidate pool of beam orientations without significant influence on the optimized beam configuration and plan quality, while selecting different starting orientations had large influence. Our study demonstrates that the algorithm can be applied to IMRT scenarios and better beam orientation configurations can be obtained using this algorithm. Furthermore, the optimization efficiency can be greatly improved through proper selection of beam orientation resolution and the starting beam orientation while guaranteeing the optimized beam configurations and plan quality.
This paper involves an unrelated parallel machine scheduling problem. Setup times are sequence dependent. A mixedinteger linear programming model that represents the system is formulated. Two measures of performance,...
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ISBN:
(数字)9781728167855
ISBN:
(纸本)9781728167855
This paper involves an unrelated parallel machine scheduling problem. Setup times are sequence dependent. A mixedinteger linear programming model that represents the system is formulated. Two measures of performance, makespan, total tardiness, and a combination of both measures, are minimize Results from a numerical example show that, with a proper weight between the two measures, a compromise solution can be found.
This paper presents a new combination of algorithms to allow coordinated movement of groups of autonomous systems in formation. A key feature of the work we will present here is a number of specific sets of fuzzy algo...
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ISBN:
(纸本)9781424453634
This paper presents a new combination of algorithms to allow coordinated movement of groups of autonomous systems in formation. A key feature of the work we will present here is a number of specific sets of fuzzy algorithms that, in combination, allow a movement in formation in 3D environments simply based on sensor inputs in a purely reactive manner. This approach is combined with a global optimization realized by using mixed integer programming to allow well planned actions of the formations with automatic avoidance of situations in which the stability of the formation could not be assured. For the combination of these two different algorithms and the possibility to extend these two with other algorithms to fulfill complicated mission tasks we we present a specific control architecture that allows to run several algorithms in parallel during a mission and to select the best performing one as the one that is controlling the autonomous vehicle.
Crowd behaviour is difficult to predict and might not be easy to translate. A number of mathematical and psychological models are proposed in the literature to investigate crowd behaviour. In this paper, we exploit mi...
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ISBN:
(纸本)9781728143064
Crowd behaviour is difficult to predict and might not be easy to translate. A number of mathematical and psychological models are proposed in the literature to investigate crowd behaviour. In this paper, we exploit mixed integer programming to model crowd behaviour with multiple time periods. This research improves upon methods by Breer et al. (2015) for determining the number of active agents and solving the problem of reducing this number by controlling reputations in a single period, under the added assumption of a reputation model of interactions (Granovetter, 1978). Thus, this paper goes on to extend the single period reputation control problem and solution to the case of multiple time periods. This class of problems requires a mixedinteger program to be solved several times with a varying constraint and a varying number of variables. This model is then supported by a promising case study of queue management at airport security gates.
This paper proposes two hybrid approaches based on the exact algorithm and metaheuristic, simulated annealing, for mixed integer programming problems. The first algorithm tries to control the tradeoff between the comp...
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ISBN:
(纸本)9780769548937;9781467346245
This paper proposes two hybrid approaches based on the exact algorithm and metaheuristic, simulated annealing, for mixed integer programming problems. The first algorithm tries to control the tradeoff between the computation time and the solution quality by reducing the number of variables of the instances to be solved by the exact algorithm. The variable reduction is performed on the basis of searching by simulated annealing in the hybrid algorithm. The second hybrid algorithm considers not only the problem size reduction but also the computation time constraint of searching for the exact algorithm. The experimental evaluation shows that the exact algorithm and SA complement each other and the second hybrid algorithm performs better than the others.
BackgroundIn Brazil, institutional foodservices are required to meet the recommendations of the Workers? Food Program (WFP), a national public policy used to plan collective menus. The current study aimed to propose a...
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BackgroundIn Brazil, institutional foodservices are required to meet the recommendations of the Workers? Food Program (WFP), a national public policy used to plan collective menus. The current study aimed to propose a mathematical model to generate a one-month menu that meets the nutritional recommendations of the WFP, with low cost and good *** considered aspects related to the eating habits of the Brazilian population, spacing of repetitions between the dishes, texture combination, and monotonicity of colors of the dishes served. A mixed integer programming model was built to formulate daily menus for an institutional foodservice for one month. The menu consisted of a base dish, a base dish option, salads (2 options), a protein dish, a protein dish option, a side dish, and a *** model ensured compliance with the recommendations proposed by the WFP and the provision of healthy and nutritionally balanced meals. The menu generated met the recommendations of the WFP, with an average of 716.97 kcal/meal, including on average 58.28% carbohydrates, 17.89% proteins, and 24.88% total fats/*** model used can help in the menu elaboration dynamics of institutional foodservices, optimizing the work of the nutritionist in charge.
The underdetermined blind source separation problem is a common problem in our daily life, but it is difficult to solve because of its underdetermined. In the literature, sparse component analysis which exploits the s...
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ISBN:
(纸本)9789811023354;9789811023347
The underdetermined blind source separation problem is a common problem in our daily life, but it is difficult to solve because of its underdetermined. In the literature, sparse component analysis which exploits the sparsity of sources in a pre-defined sparse dictionary has been proposed to solve it. Usually, sparse component analysis uses a two-stage approach. The first stage is to estimate the mixing matrix and the second stage is to reconstruct sources. In fact, the second stage is a sparse optimization problem. In this paper, we model the problem of reconstructing sources as a bi-objective optimization problem. We take the error and sparsity as the two optimization objectives, and propose an iterative algorithm based on mixed integer programming to solve the bi-objective source reconstructing problem. Experimental results show the accuracy and effectiveness of our proposed algorithm.
In this paper,a rescheduling problem involving annealing welding in a quartz glass factory is *** different mixed integer programming(MIP) formulations for the problem are presented first,and the NP-hardness of this r...
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ISBN:
(纸本)9781467397155
In this paper,a rescheduling problem involving annealing welding in a quartz glass factory is *** different mixed integer programming(MIP) formulations for the problem are presented first,and the NP-hardness of this rescheduling problem is *** the computational performance of two different MIP is ***,based on the comparison results,we discuss which MIP formulation might work better for the problem and propose the future work.
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