This study applies a penalty guided strategy and the orthogonal array test (OA) based on the Simplified Swarm Optimization algorithm (SSO) to solve the reliability redundancy allocation problems (RRAP) in the series s...
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ISBN:
(纸本)9781479919598
This study applies a penalty guided strategy and the orthogonal array test (OA) based on the Simplified Swarm Optimization algorithm (SSO) to solve the reliability redundancy allocation problems (RRAP) in the series system, the series-parallel system, the complex (bridge) system, and the overspeed protection of gas turbine system. For several decades, the RRAP has been one of the most well known techniques. The maximization of system reliability, the number of redundant components, and the reliability of corresponding components in each subsystem have to be decided simultaneously with nonlinear constraints, acting as one difficulty for the use of the RRAP. In other words, the objective function of the RRAP is the mixed-integerprogramming problem with the nonlinear constraints. The RRAP is of the class of NP-hard. Hence, in this paper, the SSO algorithm is proposed to solve the RRAP and improve computation efficiency for these NP-hard problems. There are four RRAP problems used to illustrate the applicability and the effectiveness of the SSO. The experimental results are compared with previously developed algorithms in literature. Moreover, the maximum-possible-improvement (MPI) is used to measure the amount of improvement of the solution found by the SSO to the previous solutions. According to the results, the system reliabilities obtained by the proposed SSO for the four RRAP problems are as well as or better than the previously best-known solutions.
The pooling problem is a nonconvex nonlinearprogramming problem (NLP) with applications in the refining and petrochemical industries, but also the coal mining industry. The problem can be stated as follows: given a s...
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ISBN:
(纸本)9780987214355
The pooling problem is a nonconvex nonlinearprogramming problem (NLP) with applications in the refining and petrochemical industries, but also the coal mining industry. The problem can be stated as follows: given a set of raw material suppliers (inputs) and qualities of the supplies, find a cost-minimising way of blending these raw materials in intermediate pools and outputs so as to satisfy requirements on the output qualities. The blending in two stages (in pools and outputs) introduces bilinear constraints. The pooling problem can alternatively be described as a minimum cost network flow problem with additional bilinear constraints to capture the blending of raw materials. In this paper we study a variation of the pooling problem that arises naturally in the coal mining industry and is sometimes referred to as grade targeting. Coal is made-to-order according to customers' desired product qualities. Deviations from these target qualities result in contractually agreed bonuses and penalties. In the pooling problem variation we study, costs are associated with these bonuses and penalties instead of network flows. While in the original pooling problem we have hard bounds on the qualities and unmet demand is penalised in the objective function, in our coal mining variation we have hard demand constraints and deviations from target qualities are penalised. This makes finding a feasible solution easy, while in the pooling problem finding a nontrivial feasible solution that satisfies the quality requirements is already hard. An implication of this is that we are able to solve larger problem instances than those typically studied in the pooling problem literature. To model the coal blending process accurately, we define a time-expanded network where the intermediate pools represent coal stockpiles over time. Since coal is transported in large quantities, we study the trade-off between continuous and discretized flows in coal blending, i.e., solving a continuous flow prob
In this paper, we study an extension of atomic routing games for multi-class communication networks with quality of service requirements, which can be formulated as a network management scheme. Atomic routing games ar...
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ISBN:
(纸本)9781479988549
In this paper, we study an extension of atomic routing games for multi-class communication networks with quality of service requirements, which can be formulated as a network management scheme. Atomic routing games are noncooperative games with multiple selfish players, where each player has to choose a path in a given graph to route his traffic, and then pays the corresponding cost. We develop a mixed-integer nonlinear programming model for the network management scheme in this class-based communication network. The analysis of this work offers appropriate resource allocation and a routing database identifying suitable end-to-end paths upon each connection request.
We are concerned with a capacitated location-multi allocation-routing problem in a road network with flexible travel times. It is assumed that all links are two-way and capacities of the server nodes and arcs for acce...
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This paper focuses on the schedule design problem for liner shipping to hedge against uncertainties. As a complement of Robust Optimization, a new optimization method-Wave Optimization (WO) is proposed, which is more ...
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This study applies a penalty guided strategy and the orthogonal array test (OA) based on the Simplified Swarm Optimization algorithm (SSO) to solve the reliability redundancy allocation problems (RRAP) in the series s...
详细信息
ISBN:
(纸本)9781479919611
This study applies a penalty guided strategy and the orthogonal array test (OA) based on the Simplified Swarm Optimization algorithm (SSO) to solve the reliability redundancy allocation problems (RRAP) in the series system, the series-parallel system, the complex (bridge) system, and the overspeed protection of gas turbine system. For several decades, the RRAP has been one of the most well known techniques. The maximization of system reliability, the number of redundant components, and the reliability of corresponding components in each subsystem have to be decided simultaneously with nonlinear constraints, acting as one difficulty for the use of the RRAP. In other words, the objective function of the RRAP is the mixed-integerprogramming problem with the nonlinear constraints. The RRAP is of the class of NP-hard. Hence, in this paper, the SSO algorithm is proposed to solve the RRAP and improve computation efficiency for these NP-hard problems. There are four RRAP problems used to illustrate the applicability and the effectiveness of the SSO. The experimental results are compared with previously developed algorithms in literature. Moreover, the maximum-possible-improvement (MPI) is used to measure the amount of improvement of the solution found by the SSO to the previous solutions. According to the results, the system reliabilities obtained by the proposed SSO for the four RRAP problems are as well as or better than the previously best-known solutions.
In this paper, we investigate a new bus-lane reservation problem in transportation network, which aims to optimally decide which lanes to be reserved for the exclusive use of buses and design bus transit paths for bus...
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ISBN:
(纸本)9781467365970
In this paper, we investigate a new bus-lane reservation problem in transportation network, which aims to optimally decide which lanes to be reserved for the exclusive use of buses and design bus transit paths for bus lines to achieve time-efficient bus transit with stop time window constraints. However, an exclusive bus-lane may cause negative impact on non-bus vehicles running on its adjacent non-reserved lanes as it reduces their available lanes. The objective of the problem is to minimize the total negative impact caused by reserved lanes. To address this problem, we first formulate a mixed-integer non-linear program and its complexity is proved to be NP-hard. Then, the nonlinear model is equivalently transformed into an linear one. Furthermore, properties of the problem are analyzed to reduce the search space for optimal solutions and tighten the proposed linear model. Finally, it is solved using commercial optimization software CPLEX. Computational results on randomly generated instances show the effectiveness of the proposed approach.
Water resources systems(WRS)models involve a large number of continuous and integer *** quality management problems also require the consideration of uncertainties related to the variability of flow streams and *** dy...
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Water resources systems(WRS)models involve a large number of continuous and integer *** quality management problems also require the consideration of uncertainties related to the variability of flow streams and *** dynamics are primarily *** characteristic features suggest the use of(stochastic)mixed-integerprogramming models,as well the use of sensibility analysis and ***,high dimensional real-world models and combinatorial alternatives require adequate tools for large-scale optimization *** techniques consist of decomposition methods such as the generalized Benders decomposition(GBD)and the branch-and-bound enumerative *** contribution introduces the subject of modeling WRSs by use of GBD and branch-and-bound algorithms with numerical applications.
We present Undercover, a primal heuristic for nonconvex mixed-integernonlinear programs (MINLPs) that explores a mixed-integer linear subproblem (sub-MIP) of a given MINLP. We solve a vertex covering problem to ident...
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We present Undercover, a primal heuristic for nonconvex mixed-integernonlinear programs (MINLPs) that explores a mixed-integer linear subproblem (sub-MIP) of a given MINLP. We solve a vertex covering problem to identify a smallest set of variables to fix, a so-called cover, such that each constraint is linearized. Subsequently, these variables are fixed to values obtained from a reference point, e.g., an optimal solution of a linear relaxation. Each feasible solution of the sub-MIP corresponds to a feasible solution of the original problem. We apply domain propagation to try to avoid infeasibilities, and conflict analysis to learn additional constraints from infeasibilities that are nonetheless encountered. We present computational results on a test set of mixed-integer quadratically constrained programs (MIQCPs) and MINLPs. It turns out that the majority of these instances allows for small covers. Although general in nature, we show that the heuristic is most successful on MIQCPs. It nicely complements existing root-node heuristics in different state-of-the-art solvers and helps to significantly improve the overall performance of the MINLP solver SCIP.
Railway scheduling and timetabling are common stages in the classical hierarchical railway planning process and they perhaps represent the step with major influence on user's perception about quality of service. T...
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Railway scheduling and timetabling are common stages in the classical hierarchical railway planning process and they perhaps represent the step with major influence on user's perception about quality of service. This aspect, in conjunction with their contribution to service profitability, makes them a widely studied topic in the literature, where, nowadays, many efforts are focused on improving the solving methods of the corresponding optimization problems. However, literature about models considering detailed descriptions of passenger demand is sparse. This paper tackles the problem of timetable determination by means of building and solving a nonlinearintegerprogramming model that fits the arrival and departure train times to a dynamic behavior of demand. The optimization model results are then used for computing several measures to characterize the quality of the obtained timetables considering jointly both user and company points of view. Some aspects are discussed, including the influence of train capacity and the validity of Random Incidence Theorem. An application to the C5 line of Madrid rapid transit system is presented. Different measures are analyzed in order to improve the insight into the proposed model and analyze in advance the influence of different objectives on the resulting timetable. Copyright (c) 2014 John Wiley & Sons, Ltd.
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