Developing an ace solution for two-dimensional strip packing

Dorband, John E.; Mumford, Christine L.; Wang, P.Y.

doi:10.1109/ipdps.2004.1303331

Cited by 3 publications

(4 citation statements)

References 15 publications

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“…After the basic GRASP/VND, a further post-optimization phase is performed using move forward and move backward operators. 1 On the other hand, a GA approach was introduced in [9] to solve the 1-PDP. The algorithm first starts by creating a population of feasible solutions using a new nearest-neighbor construction heuristic.…”

Section: Related Workmentioning

confidence: 99%

“…The SA Temperature Value: As previously mentioned, we use an SA acceptance criterion within the VNS to replace the current solution. To allow for an adaptive calculation of the SA starting temperature for each instance individually, we adopted the approach in [1]. The temperature is calculated based on the average value of ∆cost, where ∆cost is the difference in the objective value between some randomly generated solutions for the current problem instance.…”

Section: Stopping and Replacement Criteria For Individual Vns Runsmentioning

confidence: 99%

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Solving the One-Commodity Pickup and Delivery Problem Using an Adaptive Hybrid VNS/SA Approach

Hosny¹,

Mumford²

2010

Parallel Problem Solving From Nature, PPSN XI

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In the One-Commodity Pickup and Delivery Problem (1-PDP), a single commodity type is collected from a set of pickup customers to be delivered to a set of delivery customers, and the origins and destinations of the goods are not paired. We introduce a new adaptive hybrid VNS/SA (Variable Neighborhood Search/Simulated Annealing) approach for solving the 1-PDP. We perform sequences of VNS runs, where neighborhood sizes, within which the search is performed at each run, are adaptable. Experimental results on a large number of benchmark instances indicate that the algorithm outperforms previous heuristics in 90% of the large size test cases. Nevertheless, this comes at the expense of an increased processing time.

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Section: Related Workmentioning

confidence: 99%

Section: Stopping and Replacement Criteria For Individual Vns Runsmentioning

confidence: 99%

Solving the One-Commodity Pickup and Delivery Problem Using an Adaptive Hybrid VNS/SA Approach

Hosny¹,

Mumford²

2010

Parallel Problem Solving From Nature, PPSN XI

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show abstract

“…Ideally it is desirable to devise a scheme that is adaptable for all test cases and problem sizes, eliminating the need for (arbitrary) parameter tuning, which can be very time consuming. Following Dorband et al (2004), we created the annealing parameters for each test case individually as shown in Algorithm 1. To generate a neighboring solution s in this algorithm, a simple random swap between two different locations in s is performed.…”

Section: The Simulated Annealingmentioning

confidence: 99%

The single vehicle pickup and delivery problem with time windows: intelligent operators for heuristic and metaheuristic algorithms

Hosny

Mumford

2008

J Heuristics

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The single vehicle pickup and delivery problem with time windows is an important practical problem, yet only a few researchers have tackled it. In this research, we compare three different approaches to the problem: a genetic algorithm, a simulated annealing approach, and a hill climbing algorithm. In all cases, we adopt a solution representation that depends on a duplicate code for both the pickup request and its delivery. We also present an intelligent neighborhood move, that is guided by the time window, aiming to overcome the difficult problem constraints efficiently. Results presented herein improve upon those that have been previously published.Keywords Pickup and delivery problem with time windows · Dial-a-ride · Vehicle routing · Genetic algorithms · Simulated annealing · Hill climbingThe pickup and delivery problem with time windows (PDPTW) is an important practical problem that is likely to assume even greater prominence in the future. Current concerns over global warming, resource depletion and the social impact of traffic congestion and pollution (and resulting legislation, increase in cost, and changes in public perceptions) are driving companies, government organizations and researchers to improve the efficiency of logistics and distribution operations. In addition, the rapid growth in parcel transportation as a result of e-commerce is likely to have an increasing impact. More cooperation between manufacturers, shippers and carriers in supply chains could greatly reduce the environmental impact of transport (the number of M.I. Hosny ( ) ·

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“…However, it places some difficult constraints on the programmer to find and exploit the parallelism in a program. aCe (the adaptive C extension) [5] is an excellent example of a programming language that uses explicit parallelism. In aCe, threads are treated as arrays of records.…”

Section: Explicit Parallelismmentioning

confidence: 99%

Automatic resource management using an adaptive parallelism environment

Wangerin

Scherson

Proceedings International Parallel and Distributed Processing Symposium

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The Adaptive Parallelism Environment is introduced as a means of effectively utilizing MPP processing resources in a multi-programmed MIMD or distributed system. It achieves this by dynamically calculating the optimal number of threads for a given program at runtime. The optimality calculation considers both the number of processing elements available to handle additional workloads and the estimated computational speedup gained by using additional threads versus the communications overhead of using additional threads. The Adaptive Parallelism Environment is composed of three sections: a load balancer, which migrates threads and provides information regarding the availability of processing elements, a code analyzer, which estimates the number and composition of instructions in a potential thread as well as the number of communications needed to synchronize the potential thread, and a runtime environment, which gathers information from the load balancer and code analyzer and performs the runtime calculations to estimate the optimal number of threads.

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Developing an ace solution for two-dimensional strip packing

Cited by 3 publications

References 15 publications

Solving the One-Commodity Pickup and Delivery Problem Using an Adaptive Hybrid VNS/SA Approach

Solving the One-Commodity Pickup and Delivery Problem Using an Adaptive Hybrid VNS/SA Approach

The single vehicle pickup and delivery problem with time windows: intelligent operators for heuristic and metaheuristic algorithms

Automatic resource management using an adaptive parallelism environment

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