In this paper, a penalty function method for multiobjective interval bilevel linear programming (MIBLP) problem is proposed. Firstly, interval order relation is used to transform objective functions. The possibility l...
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We establish a linear programming formulation for the solution of joint chance constrained optimal control problems over finite time horizons. The joint chance constraint may represent an invariance, reachability or r...
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We derive a linear programming bound on the maximum cardinality of error-correcting codes in the sum-rank metric. Based on computational experiments on relatively small instances, we observe that the obtained bounds o...
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In modern supermarkets, given the limited shelf life and the propensity for rapid declines in the sales of perishable goods, such as vegetables, it becomes imperative to conduct daily restocking based on historical sa...
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ISBN:
(数字)9798350370805
ISBN:
(纸本)9798350370812
In modern supermarkets, given the limited shelf life and the propensity for rapid declines in the sales of perishable goods, such as vegetables, it becomes imperative to conduct daily restocking based on historical sales and consumer demand to preclude the occurrence of undersold items the following day. Consequently, conducting restocking and pricing strategies based on sales and demand holds significant research importance for supermarkets. This study initially employs a multiple linear regression model to investigate the impact on profit by adjusting total sales (Q), sales price (P), and each component of cost-plus pricing (C, T, L, A), thereby determining the relationship between total sales and cost-plus pricing for each vegetable category, as well as the functional relationship between total sales and cost-plus pricing for each vegetable category. Based on the derived functional relationship, time series prediction and linear programming models are utilized to forecast the market demand for each vegetable category over a one-week period, subsequently formulating the daily restocking plan and pricing strategy for each vegetable category in the subsequent week to maximize supermarket profit while satisfying market demand. Finally, an analysis of saleable vegetable items reveals that 29 vegetable items can be displayed, with a total profit of 846.35 yuan. Upon testing the sales data of 300,000 vegetables, compared to the conventional display method sans the use of this model, the overall profit margin surged by 269.75 yuan, an increment of 47% relative to the initial profit, effectively enhancing the operational efficiency and profitability of the supermarket.
The purpose of this work is to develop a master surgical scheduling for a case study of a large-scale public hospital in Thailand using a mixed-integer linear programming model (MILP) and a genetic algorithm (GA). Due...
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ISBN:
(数字)9798331520038
ISBN:
(纸本)9798331520045
The purpose of this work is to develop a master surgical scheduling for a case study of a large-scale public hospital in Thailand using a mixed-integer linear programming model (MILP) and a genetic algorithm (GA). Due to the high volume of operations that must be handled every day, our main objective is to create a schedule that maximizes OR utilization, minimizes room overtime, and reduces idle time between surgical patients. The data from Thammasat University Hospital were analyzed and simulated to generate a timetable from daily to weekly schedule. Our results show that an exact solution can be obtained by MILP for a simple problem while a large CPU run time is incurred for the complex problems. GA provided the optimal solution for a complex large-scale problem. The schedule generated by the proposed GA is more flexible and the staff can improve it to obtain more practical timetable in real-life situations, such as increasing the number of surgeries, setting a time block for specific surgical specialties, and handling emergency cases.
In the literature one can find various methods for solving full fuzzy linear programming problems. Very few of them fully comply to the extension principle. In the current study we extend an existing solution approach...
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ISBN:
(数字)9788396960160
ISBN:
(纸本)9798350359718
In the literature one can find various methods for solving full fuzzy linear programming problems. Very few of them fully comply to the extension principle. In the current study we extend an existing solution approach based on the extension principle to derive fuzzy-set optimal results to full fuzzy linear programming problems with L-R fuzzy *** approach is a twofold extension of a procedure from the literature: (i) it employs L-R membership functions in the optimization models that derive fuzzy-set optimal objective values; and (ii) it introduces new optimization models for deriving fuzzy-set optimal solution values in accordance to the extension principle and product operator. The employment of the product operator makes the derived fuzzy-set results more thinner, thus more appropriate to further decision making.
The rate vs. distance problem is a long-standing open problem in coding theory. Recent papers have suggested a new way to tackle this problem by appealing to a new hierarchy of linear programs. If one can find good du...
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To meet stringent performance requirements, communication networks are becoming increasingly programmable and flexible, supporting fast and frequent adjustments. However, reconfiguring networks in a dependable and tra...
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ISBN:
(数字)9798350383508
ISBN:
(纸本)9798350383515
To meet stringent performance requirements, communication networks are becoming increasingly programmable and flexible, supporting fast and frequent adjustments. However, reconfiguring networks in a dependable and transiently consistent manner is known to be algorithmically challenging. This paper revisits the fundamental problem of how to update the routes in a network in a (transiently) loop-free manner, considering both the Strong Loop-Freedom (SLF) and the Relaxed Loop-Freedom (RLF) *** present two fast algorithms to solve the SLF and RLF problem variants exactly, to optimality. Our algorithms are based on a parameterized integer linear program which would be intractable to solve directly by a classic solver. Our main technical contribution is a lazy cycle breaking strategy which, by adding constraints lazily, improves performance dramatically, and outperforms the state-of-the-art exact algorithms by an order of magnitude on realistic medium-sized networks. We further explore approximate algorithms and show that while a relaxation approach is relatively slow, with a local search approach short update schedules can be found, outperforming the state-of-the-art *** the theoretical front, we also provide an approximation lower bound for the update time of the state-of-the-art algorithm in the literature. As a contribution to the research community, we made all our code and implementations publicly available.
The global drive towards carbon neutrality has led to a significant increase in the number of power plants based on renewable energy sources (RES). Concurrently, numerous households are adopting RES to generate their ...
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This paper proposes two approaches for reducing the impact of the error floor phenomenon when decoding quantum low-density parity-check codes with belief propagation based algorithms. First, a low-complexity syndrome-...
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ISBN:
(数字)9781728190549
ISBN:
(纸本)9781728190556
This paper proposes two approaches for reducing the impact of the error floor phenomenon when decoding quantum low-density parity-check codes with belief propagation based algorithms. First, a low-complexity syndrome-based linear programming (SB- LP) decoding algorithm is proposed, and second, the proposed SB-LP is applied as a post-processing step after syndrome-based min-sum (SB-MS) decoding. For the latter case, a new early stopping criterion is introduced to decide when to activate the SB- LP algorithm, avoiding executing a predefined maximum number of iterations for the SB-MS decoder. Simulation results show, for a sample hypergraph code, that the proposed decoder can lower the error floor by two to three orders of magnitude compared to SB-MS for the same total number of decoding iterations.
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