This paper investigates single-machine scheduling problem, which is an NP-hard problem, with deteriorating jobs and different due dates tominimize total tardiness. First, two special polynomially solvable cases of the...
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This paper investigates single-machine scheduling problem, which is an NP-hard problem, with deteriorating jobs and different due dates tominimize total tardiness. First, two special polynomially solvable cases of the problem and a mixed-integerprogramming (MIP) model are proposed. Since the large-scale problem needs a long time when the MIP is solved using the CPLEX, the improved estimation of distribution algorithm (EDA) is proposed to solve the problem with a large size. EDA depends on the probabilistic model, which denotes the distribution of decision variables in the feasible region space. Meanwhile, EDA owns efficient search capability and convergence. To obtain an improved initial population, an efficient initialization scheme based on the feature of two special cases and a heuristic algorithm are adopted in the process of constructing the initial population. The probabilistic model is composited based on elite solutions from each generation. Simultaneously, mutation is embedded tomaintain the diversity of the population. Compared with the results, numerical experiments show that the proposed algorithm can obtain good near-optimal solutions within a short period.
We consider the problem of designing a reconfigurable machining line. Such a line is composed of a sequence of workstations performing specific sets of operations. Each workstation is comprised of several identical CN...
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We consider the problem of designing a reconfigurable machining line. Such a line is composed of a sequence of workstations performing specific sets of operations. Each workstation is comprised of several identical CNC machines (machining centers). The line is required to satisfy the given precedence order, inclusion, exclusion and accessibility constraints on the given set of operations. Inclusion and exclusion are zoning constraints which oblige or forbid certain operations to be performed on the same workstation. The accessibility constraints imply that each operation has a set of possible part positions under which it can be performed. All the operations performed on the same workstation must have a common part position. Workstation times are computed taking into account processing and setup times for operations and must not exceed a given bound. The number of CNC machines at one workstation is limited, and the total number of machines must be minimized. A genetic algorithm is proposed. This algorithm is based on the permutation representation of solutions. A heuristic decoder is suggested to construct a solution from a permutation, so that the output solution is feasible w.r.t. precedence, accessibility, cycle time, and exclusion constraints. The other constraints are treated with a penalty approach. For a local improvement of solutions, a mixed integer programming model is suggested for an optimal design of workstations if the order of operations is fixed. An experimental evaluation of the proposed GA on large scale test instances is performed. (C) 2012 Elsevier Ltd. All rights reserved.
In this work we present a stochastic programmingmodel minimizing costs, to support the decision process of inventory policy which best satisfies the demand for food in shelters when hurricane winds are about to impac...
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Seamless steel tube, including multi-variety and multi-specification products, requires variously complicated operations in the whole production process, especially in the cold treating process (CTP). This paper takes...
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ISBN:
(纸本)9781424473281
Seamless steel tube, including multi-variety and multi-specification products, requires variously complicated operations in the whole production process, especially in the cold treating process (CTP). This paper takes the seamless tube plant of Baoshan Iron and Steel Complex as the research background. Considering the practical production constraints, CTP scheduling problem can be viewed as a hybrid flowshop scheduling problem with sequence-dependent setup time. We formulate it as a non-linear mixed integer programming model(NMIP) with multi-objectives. Then a two-stage heuristic algorithm based on modified GA and local search method is proposed to get near-optimal solution of large-scale NMIP problem. Finally, computation experiments with real production instance are carried out to test the efficiency and performance of algorithm. The simulation results show that proposed model and algorithm can be implemented as an effective method to generate optimized scheduling scheme in the CTP scheduling system.
Crossdocking is a warehousing strategy that moves products through flow consolidation centers or crossdocks without putting them into storage. To address various decision problems associated with crossdocking operatio...
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ISBN:
(纸本)9781424468508
Crossdocking is a warehousing strategy that moves products through flow consolidation centers or crossdocks without putting them into storage. To address various decision problems associated with crossdocking operations planning and scheduling, a careful modeling of the entire crossdocking operation is a prerequisite. This paper describes the development of a novel resource-constrained crossdocking model to address an important crossdocking planning problem which is the scheduling of trucks at crossdocking terminals. A mixedintegerprogramming (MIP) model is proposed to formulate the truck scheduling problem. For the lack of real test data, the procedure of generating synthetic data is discussed and its compatibility to real-world applications is justified. The paper also discusses whether the crossdock capacity is a bottleneck resource in the operation of truck scheduling or not. The steps mentioned above build a realistic reliable framework to design and evaluate various sort of algorithms for this combinatorial optimization problem as our future work.
The mining programming of accumulated bauxite should comprehensively consider the site selection and rational utilization of resources. The mixed integer programming model on optimization of site selection and rationa...
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ISBN:
(纸本)9780769539102
The mining programming of accumulated bauxite should comprehensively consider the site selection and rational utilization of resources. The mixed integer programming model on optimization of site selection and rational ore blending was constructed on the basis of the theories of logistics planning, operations research, etc. Take Taipingbei mine in Pingguo bauxite as the example, the results which were calculated by the operations research software Xpress-MP show that the model is rationality and feasible. The mathematical model is of great importance to the sustainable utilization of the bauxite resources, increasing mine service life and raising economic benefit of enterprises.
Due to the growing environmental pressure and resource antinomy, increasing attention is given to the reverse logistics. In this paper, a collection model based on circular economy, which is oriented to the third part...
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ISBN:
(纸本)9781424420124
Due to the growing environmental pressure and resource antinomy, increasing attention is given to the reverse logistics. In this paper, a collection model based on circular economy, which is oriented to the third party reverse logistics, is proposed. The model, called mixed integer programming model, is solved by an algorithm based on Lagrangian heuristics. A numerical example is given to illustrate the rationality of the model and efficiency of algorithm.
We propose a mixed integer programming model to minimize the maximum storage space requirement over an infinite time horizon by offsetting the inventory cycles of items. We also develop a genetic algorithm to find the...
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We propose a mixed integer programming model to minimize the maximum storage space requirement over an infinite time horizon by offsetting the inventory cycles of items. We also develop a genetic algorithm to find the near-optimal solution. The mixed integer programming model and the genetic algorithm produce better results than the existing heuristic. We also develop a mixed integer programming model for the finite time horizon;this model is more general and realistic than that for the infinite time horizon. A warehouse management system is designed based on the algorithms we developed. Significance: We provide both a mixedinteger program and a genetic algorithm to minimize the maximum storage space requirement for the warehouse. These methods can be practically implemented at warehouses and distribution centers for the utilization of the storage space and other resources.
Due to the growing environmental pressure and resource antinomy,increasing attention is given to the reverse *** this paper,a collection model based on circular economy,which is oriented to the third party reverse log...
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Due to the growing environmental pressure and resource antinomy,increasing attention is given to the reverse *** this paper,a collection model based on circular economy,which is oriented to the third party reverse logistics,is *** model,called mixed integer programming model,is solved by an algorithm based on Lagrangian heuristics.A numerical example is given to illustrate the rationality of the model and efficiency of algorithm.
Routing optimization provides network operators with a powerful method for traffic engineering. Its general objective is to distribute traffic flows evenly across available network resources in order to avoid network ...
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Routing optimization provides network operators with a powerful method for traffic engineering. Its general objective is to distribute traffic flows evenly across available network resources in order to avoid network congestion and quality of service degradation. In this paper we consider routing optimization based on conventional routing protocols where packets are forwarded hop-by-hop in a destination-based manner. Unlike other work. in this area, we consider routing protocols, which are able to take into account concave routing metrics in addition to additive ones. The concave link metric introduces,an additional degree of freedom for routing optimization, thus, increasing its optimization potential. We present and evaluate a mixed-integerprogrammingmodel, which works on these metrics. This model unifies the optimization for single-metric and dual-metric routing concepts and also includes the consideration of multipath routing. Furthermore, we propose a heuristic algorithm usable for larger network instances. Numerical results indicate that employment of both the dual-metric concept and multipath routing can achieve considerably better utilization results than default-configured single-metric routing. A significant finding is that metric-based routing optimization with two link metrics often comes close to the results obtainable by optimization of arbitrarily configurable routing.
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