The Experts below are selected from a list of 122700 Experts worldwide ranked by ideXlab platform
Duanbing Chen - One of the best experts on this subject based on the ideXlab platform.
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a new Heuristic Algorithm for rectangle packing
Computers & Operations Research, 2007Co-Authors: Wenqi Huang, Duanbing ChenAbstract:The rectangle packing problem often appears in encasement and cutting as well as very large-scale integration design. To solve this problem, many Algorithms such as genetic Algorithm, simulated annealing and other Heuristic Algorithms have been proposed. In this paper, a new Heuristic Algorithm is recommended based on two important concepts, namely, the corner-occupying action and caving degree. Twenty-one rectangle-packing instances are tested by the Algorithm developed, 16 of which having achieved optimum solutions within reasonable runtime. Experimental results demonstrate that the Algorithm developed is fairly efficient for solving the rectangle packing problem.
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An efficient Heuristic Algorithm for rectangle-packing problem
Simulation Modelling Practice and Theory, 2007Co-Authors: Wenqi Huang, Duanbing ChenAbstract:Abstract Rectangle-packing problem involves many industrial applications, such as shipping, timber cutting, very large scale integration (VLSI) floor planning, and so on. This problem has shown to be NP hard, and many Algorithms such as genetic Algorithm, simulated annealing and other Heuristic Algorithms are presented to solve it. Based on the wisdom and experience of human being, an efficient Heuristic Algorithm is proposed in this paper. Two group benchmarks are used to test the performance of the produced Algorithm, 19 instances of first group and 3 instances of second group having achieved optimal solutions. The experimental results demonstrate that the presented Algorithm is rather efficient for solving the rectangle-packing problem.
Wenqi Huang - One of the best experts on this subject based on the ideXlab platform.
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a new Heuristic Algorithm for rectangle packing
Computers & Operations Research, 2007Co-Authors: Wenqi Huang, Duanbing ChenAbstract:The rectangle packing problem often appears in encasement and cutting as well as very large-scale integration design. To solve this problem, many Algorithms such as genetic Algorithm, simulated annealing and other Heuristic Algorithms have been proposed. In this paper, a new Heuristic Algorithm is recommended based on two important concepts, namely, the corner-occupying action and caving degree. Twenty-one rectangle-packing instances are tested by the Algorithm developed, 16 of which having achieved optimum solutions within reasonable runtime. Experimental results demonstrate that the Algorithm developed is fairly efficient for solving the rectangle packing problem.
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An efficient Heuristic Algorithm for rectangle-packing problem
Simulation Modelling Practice and Theory, 2007Co-Authors: Wenqi Huang, Duanbing ChenAbstract:Abstract Rectangle-packing problem involves many industrial applications, such as shipping, timber cutting, very large scale integration (VLSI) floor planning, and so on. This problem has shown to be NP hard, and many Algorithms such as genetic Algorithm, simulated annealing and other Heuristic Algorithms are presented to solve it. Based on the wisdom and experience of human being, an efficient Heuristic Algorithm is proposed in this paper. Two group benchmarks are used to test the performance of the produced Algorithm, 19 instances of first group and 3 instances of second group having achieved optimal solutions. The experimental results demonstrate that the presented Algorithm is rather efficient for solving the rectangle-packing problem.
David J. Rader - One of the best experts on this subject based on the ideXlab platform.
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A Heuristic Algorithm for a chance constrained stochastic program
European Journal of Operational Research, 2007Co-Authors: Concetta A. Depaolo, David J. RaderAbstract:A chance constrained stochastic program is considered that arises from an application to college enrollments and in which the objective function is the expectation of a linear function of the random variables. When these random variables are independent and normally distributed with mean and variance that are linear in the decision variables, the deterministic equivalent of the problem is a nonconvex nonlinear knapsack problem. The optimal solution to this problem is characterized and a greedy-type Heuristic Algorithm that exploits this structure is employed. Computational results show that the Algorithm performs well, especially when the normal random variables are approximations of binomial random variables.
Chingwu Chu - One of the best experts on this subject based on the ideXlab platform.
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a Heuristic Algorithm for the truckload and less than truckload problem
European Journal of Operational Research, 2005Co-Authors: Chingwu ChuAbstract:Abstract The delivery of goods from a warehouse to local customers is an important and practical problem of a logistics manager. In reality, we are facing the fluctuation of demand. When the total demand is greater than the whole capacity of owned trucks, the logistics managers may consider using an outsider carrier. Logistics managers can make a selection between a truckload (a private truck) and a less-than-truckload carrier (an outsider carrier). Selecting the right mode to transport a shipment may bring significant cost savings to the company. In this paper, we address the problem of routing a fixed number of trucks with limited capacity from a central warehouse to customers with known demand. The objective of this paper is developing a Heuristic Algorithm to route the private trucks and to make a selection of less-than-truckload carriers by minimizing a total cost function. Both the mathematical model and the Heuristic Algorithm are developed. Finally, some computational results and suggestions for future research are presented.
Konstantinos N Androutsopoulos - One of the best experts on this subject based on the ideXlab platform.
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a Heuristic Algorithm for solving hazardous materials distribution problems
European Journal of Operational Research, 2004Co-Authors: Konstantinos G Zografos, Konstantinos N AndroutsopoulosAbstract:A type of decision of major importance that directly affects the performance of a distribution system is the routing and scheduling of delivery trucks. The determination of hazardous materials distribution routes can be defined as a bi-objective vehicle routing problem with time windows since risk minimization accompanies the cost minimization in the objective function. The objective of this paper is to present a new Heuristic Algorithm for solving the bi-objective vehicle routing and scheduling problem. The proposed Algorithm has been applied to several benchmark problems. The results of these applications seem to be quite encouraging. Furthermore, the proposed Algorithm has been integrated within a GIS based decision support system for hazardous materials logistics operations providing valid preliminary results on a set of case studies.
