Towards Quick Solutions for Generalized Placement Problem

Srinivasan, S.; Kamakoti, V.; Bhattacharya, Arnab

doi:10.1109/ised.2011.21

Cited by 4 publications

(2 citation statements)

References 48 publications

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“…The slot-placement problem can be formulated as a quadratic assignment problem [21], [22], which is known as an NP-hard problem. The sub-optimal solutions are usually obtained by using simulated annealing (SA), branch and bound methods, genetic algorithm and tabu search [23], [24].…”

Section: Constrained Slot Placement Problemmentioning

confidence: 99%

Solving Constrained Slot Placement Problems Using an Ising Machine and Its Evaluations

Kanamaru

Kawamura

Tanaka

et al. 2021

IEICE Trans. Inf. & Syst.

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Ising machines have attracted attention, which is expected to obtain better solutions of various combinatorial optimization problems at high speed by mapping the problems to natural phenomena. A slotplacement problem is one of the combinatorial optimization problems, regarded as a quadratic assignment problem, which relates to the optimal logic-block placement in a digital circuit as well as optimal delivery planning. Here, we propose a mapping to the Ising model for solving a slotplacement problem with additional constraints, called a constrained slotplacement problem, where several item pairs must be placed within a given distance. Since the behavior of Ising machines is stochastic and we map the problem to the Ising model which uses the penalty method, the obtained solution does not always satisfy the slot-placement constraint, which is different from the conventional methods such as the conventional simulated annealing. To resolve the problem, we propose an interpretation method in which a feasible solution is generated by post-processing procedures. We measured the execution time of an Ising machine and compared the execution time of the simulated annealing in which solutions with almost the same accuracy are obtained. As a result, we found that the Ising machine is faster than the simulated annealing that we implemented.

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Section: Constrained Slot Placement Problemmentioning

confidence: 99%

Solving Constrained Slot Placement Problems Using an Ising Machine and Its Evaluations

Kanamaru

Kawamura

Tanaka

et al. 2021

IEICE Trans. Inf. & Syst.

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show abstract

“…The slot-placement problem can be applied to many practical optimization problems such as labor shift scheduling and FPGA logic-block placement [18], [19]. It can be considered to be a variation of quadratic assignment problems, which are known as an NP-hard problem [20], and has been solved using simulated annealing (SA) [21] and branch-and-bound methods [22]. A method for mapping the slot-placement problem to the QUBO model and solving it using an Ising machine has also been proposed [16].…”

Section: B Slot-placement Problemmentioning

confidence: 99%

A Three-Stage Annealing Method Solving Slot-Placement Problems Using an Ising Machine

et al. 2021

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Ising machines are promising alternatives to solve combinatorial optimization problems, which search for their quasi-optimal solutions with high speed and high accuracy. However, the obtained solution much depends on the initial spin states, since the computation time is finite. Moreover, due to their probabilistic nature, they cannot always satisfy the constraints given to combinatorial optimization problems. In this paper, we propose a three-stage annealing method, targeting a slot-placement problem as a typical but difficult example of combinatorial optimization problems. The proposed method is composed of an initial process, an annealing process, and a correction process. The initial process and the correction process are executed by a classical computer while the annealing process is executed by an Ising machine. In the initial process, we give initial spin values that lead to a relatively good solution to the combinatorial optimization problem, which satisfies the given constraints. Then, the annealing process is executed by an Ising machine, and the solution obtained by the annealing process is further corrected to satisfy the constraints. The experimental results demonstrate that the proposed method reduces a minimum total weighted wiring length by 0.0898%-2.45% on average depending on the initial process methods used, compared to the existing method. The mean total weighted wiring length is reduced by 2.79%-7.08% on average depending on the initial process methods used.

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Mapping Constrained Slot-Placement Problems to Ising Models and its Evaluations by an Ising Machine

Kanamaru

Kawamura

Tanaka

et al. 2019

2019 IEEE 9th International Conference on Consumer Electronics (ICCE-Berlin)

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Towards Quick Solutions for Generalized Placement Problem

Cited by 4 publications

References 48 publications

Solving Constrained Slot Placement Problems Using an Ising Machine and Its Evaluations

Solving Constrained Slot Placement Problems Using an Ising Machine and Its Evaluations

A Three-Stage Annealing Method Solving Slot-Placement Problems Using an Ising Machine

Mapping Constrained Slot-Placement Problems to Ising Models and its Evaluations by an Ising Machine

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