Mixed Integer Programming Formulations for Steiner Tree and Quality of Service Multicast Tree Problems

This article presents a flow-based mixed integer programming formulation for the Quality of Service Multicast Tree problem. This is a relevant problem related to nowadays telecommunication networksto distribute multimedia over cloud-based Internet systems. To the best of our knowledge, no previous mixed integer programming formulation was proposed for Quality of Service Multicast Tree Problem. Experimental evaluation is performed over a set of realistic problem instances from SteinLib, to prove that standard exact solvers can find solutions to real-world size instances. Exact method is applied for benchmarking the proposed formulations, finding optimal solutions and low feasible-to-optimal gaps in reasonable execution times.

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PRUNING REDUNDANT SERVICES FOR FAST SERVICE SELECTION

International Journal of Computational Methods ◽

10.1142/s0219876213500369 ◽

2013 ◽

Vol 10 (06) ◽

pp. 1350036

Author(s):

S. G. WANG ◽

Z. P. LIU ◽

Q. B. SUN ◽

H. ZOU ◽

F. C. YANG

Keyword(s):

Quality Of Service ◽

Integer Programming ◽

Mixed Integer Programming ◽

Service Selection ◽

Search Space ◽

Mixed Integer ◽

Time Cost ◽

Test Bed ◽

Optimal Service

Selecting the optimal service from a mass of functionally equivalent services with low time cost is significant. Previous research addressed this issue excessively relying on several kinds of optimization algorithms. In this work, we propose an approach that prunes redundant services and reduces search space of service selection on the basis of Skyline computing and context inference. We firstly adopt Skyline computing to prune redundant services. Then, we present the notion of context service based on context inference to further reduce the size of service selection problem. Finally, mixed integer programming is employed to find the optimal service from context services according to users' Quality of Service (QoS) requirements. Experimental results on a test bed indicate that our approach can find the optimal service with low time cost.

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Application of Mixed-Integer Programming and Dispatching Rules on Parallel Machine Scheduling with Inserted Idle Time

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.437.748 ◽

2013 ◽

Vol 437 ◽

pp. 748-751

Author(s):

Chi Yang Tsai ◽

Yi Chen Wang

Keyword(s):

Integer Programming ◽

Mixed Integer Programming ◽

Parallel Machines ◽

Optimal Solution ◽

Parallel Machine Scheduling ◽

Idle Time ◽

Dispatching Rules ◽

Mixed Integer ◽

Scheduling Problems

This research considers the problem of scheduling jobs on unrelated parallel machines with inserted idle times to minimize the earliness and tardiness. The aims at investigating how particular objective value can be improved by allowing machine idle time and how quality solutions can be more effectively obtained. Two mixed-integer programming formulations combining with three dispatching rules are developed to solve such scheduling problems. They can easy provide the optimal solution to problem involving about nine jobs and four machines. From the results of experiments, it is found that: (1) the inserted idle times decreases objective values more effectively; (2) three dispatching rules are very competitive in terms of efficiency and quality of solutions.

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