N-1-1 contingency analysis considers the consecutive loss of two elements in a power system, with intervening time for operator adjustments;the associated reliability criterion was recently included in the NERC Standa...
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ISBN:
(纸本)9781467327275
N-1-1 contingency analysis considers the consecutive loss of two elements in a power system, with intervening time for operator adjustments;the associated reliability criterion was recently included in the NERC Standard TPL-001-1. In this paper, we introduce optimization models for N-1-1 contingency analysis, based on DC optimal power flow considerations. We use mixed-integerprogramming approaches to optimally model the system adjustments required to avoid potential cascading outages during the primary and secondary contingencies. Contingencies are determined via worst-case interdiction analysis. To facilitate operation during the secondary contingency, line overloads and load shedding are allowed. We test our models and algorithms on several IEEE test systems. Our computational experiments indicate potential for the models to augment comprehensive system operations models, such as unit commitment.
This paper proposes a task scheduling method withstanding practical use in the sense that communication time constraint of distributed processing is addressed appropriately. The communication time constraint is formul...
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This paper proposes a task scheduling method withstanding practical use in the sense that communication time constraint of distributed processing is addressed appropriately. The communication time constraint is formulated appropriately based on mixed integer programming. The validity of the proposed method is verified through a real machines experiment.
This paper studies two-stage cross docking logistics optimization problem with the objective to minimize the makespan, in which we analyze a model with multiple suppliers and clients, and one warehouse that employs cr...
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ISBN:
(纸本)9781424415304
This paper studies two-stage cross docking logistics optimization problem with the objective to minimize the makespan, in which we analyze a model with multiple suppliers and clients, and one warehouse that employs cross docking which operating multiple inbound vehicles and one outbound vehicle. A mixed integer programming (MIP) is first built and then solved by CPLEX for small scale instances. Moreover, two heuristics are constructed to observe the performance for moderate and large scale instances. Two lower bounds are further presented to compare with the two heuristics. Finally, computational experiments are carefully designed to illustrate and compare these approaches.
We consider the generalized minimum edge-biconnected network problem where the nodes of a graph are partitioned into clusters and exactly one node from each cluster is required to be connected in an edge-biconnected w...
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We consider the generalized minimum edge-biconnected network problem where the nodes of a graph are partitioned into clusters and exactly one node from each cluster is required to be connected in an edge-biconnected way. Instances of this problem appear, for example, in the design of survivable backbone networks. We present different variants of a variable neighborhood search approach that utilize different types of neighborhood structures, each of them addressing particular properties as spanned nodes and/or the edges between them. For the more complex neighborhood structures, we apply efficient techniques such as a graph reduction to essentially speed up the search process. For comparison purposes, we use a mixedinteger linear programming formulation based on multi-commodity flows to solve smaller instances of this problem to proven optimality. Experiments on such instances indicate that the variable neighborhood search is also able to identify optimal solutions in the majority of test runs, but within substantially less time. Tests on larger Euclidean and random instances with up to 1,280 nodes, which could not be solved to optimality by mixed integer programming, further document the efficiency of the variable neighborhood search. In particular, all proposed neighborhood structures are shown to contribute significantly to the search process. (C) 2010 Wiley Periodicals, Inc. NETWORKS, Vol. 55(3), 256-275 2010
＜正＞In this paper,we address the scheduling problem involving batch processing machines. The presented mixed integer programming formulation first provides an elegant model for the problem under ***,it enables solut...
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＜正＞In this paper,we address the scheduling problem involving batch processing machines. The presented mixed integer programming formulation first provides an elegant model for the problem under ***,it enables solutions to the problem instances beyond the capability of exact methods developed so *** order to alleviate computational burden,we propose MlP-based approaches which balance solution quality and computing time.
This paper mainly uses linear regression analysis, ARIMA model, greedy algorithm and other methods to solve the main problems such as how to accurately predict the sales trend, effectively make the replenishment plan ...
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ISBN:
(纸本)9798400716775
This paper mainly uses linear regression analysis, ARIMA model, greedy algorithm and other methods to solve the main problems such as how to accurately predict the sales trend, effectively make the replenishment plan and reasonable price strategy. This study collected various data of vegetable sales in a shopping mall in two years. The box plot is used for data preprocessing, the data is visualized, and the outliers are removed. First, predict the sales volume of each vegetable category from July 1 to *** ARIMA model is used to predict the price, and the adjusted grid model is used to predict the price and give the daily replenishment strategy for the next week. Further make sales forecast, replenishment and pricing decision of each vegetable item on July 1. And the data is preprocessed by average value, and the item number without transaction information is screened out. Then the problem is transformed into knapsack problem (a combinatorial optimization NP-complete problem) and solved by dynamic programming. Next, the collected loss rate data are introduced to further clean, screen and modify the previously processed data to establish the correlation between loss rate and shelf life, so as to establish a new model. Finally, the greedy algorithm is used to give the optimal solution, select 33 goods with the highest expected profit, and finally give the pricing strategy on July 1, 2023.
The problem of distribution centers location with multiple practical constraints, such as soft service time window, rigid work time window, vehicle being reused and so on, is shown firstly. Secondly, a multi-factor in...
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The problem of distribution centers location with multiple practical constraints, such as soft service time window, rigid work time window, vehicle being reused and so on, is shown firstly. Secondly, a multi-factor integrated optimization model is given, which not only optimizes distribution centers location and vehicle routes, but also meets all the multiple practical constraints. A bi-level nested genetic algorithm is proposed thirdly, where the design of the lower algorithm meets various constraints of optimization. Finally, the feasibility of the model and the efficiency of the algorithm are tested by a numerical example.
Based on observations made in a cabinet manufacturing plant, a multi-objective mixed integer programming model for coordinated warehouse order picking and production scheduling is proposed. To minimize production make...
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Based on observations made in a cabinet manufacturing plant, a multi-objective mixed integer programming model for coordinated warehouse order picking and production scheduling is proposed. To minimize production makespan and total picking time in the warehouse, a non-dominated sorting GA-II (NSGA-II) with a modified PMX crossover and inverse, insert, swap mutation operators is used. Compared to the solutions found by Gurobi 7.0, GA obtains a more diverse and higher quality set of non-dominated solutions. Moreover, it is observed (but not proved) that in an optimal solution, the sequence of jobs and that of picking components for those jobs are structurally related.
Detailed scheduling of a packing hall consisting of a number of packing lines is a problem encountered in many process industries. The scheduling problem is complicated by the presence of sequence dependent changeover...
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Detailed scheduling of a packing hall consisting of a number of packing lines is a problem encountered in many process industries. The scheduling problem is complicated by the presence of sequence dependent changeovers of different lengths. Vehicle routing problems (VRP) arise in many distribution, product inventory, and mobile repair industries. A common objective is to find a route for a vehicle, which satisfies a variety of constraints, and so as to minimise the total vehicle operating cost. In other applications, it may be important to minimise the total time. Little work has been done on the solution of the large-scale design/scheduling/sequencing problems using VRP type formulations. A model for this problem has been presented and its computational performance is compared with other classical disjunctive formulations. The approach presented here is based on a continuous-time formulation in that all events (packing and changeovers) are allowed to start and end at any time. The proposed approach has excellent integrality property, as it does not contain any 'big M'. type of constraints encountered in these problems. This problem is formulated as a mixedinteger program and solved using a standard solver, which makes the proposed approach attractive commercially. The details of the formulation and the results of a large-scale commercial packing hall problem are given.
An algorithm is developed to optimize vehicle speed trajectory over multiple signalized intersections with known traffic signal information to minimize fuel consumption and travel time, and to meet ride comfort requir...
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ISBN:
(纸本)9781509045839
An algorithm is developed to optimize vehicle speed trajectory over multiple signalized intersections with known traffic signal information to minimize fuel consumption and travel time, and to meet ride comfort requirements using sequential convex optimization method. A comparison between the proposed method and dynamic programming is carried out to verify its optimality. In addition, vehicle motion during turning is studied because of its significant effect on fuel consumption and travel time.
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