For a specific query merging the returned results from multiple search engines, in theform of a metasearch aggregation, can provide significant improvement in the quality ofrelevant documents. This paper suggests a minimax linear programming (LP) formulation forfusion of multiple search engines results. The paper proposes a weighting method toinclude the importance weights of the underlying search engines. This is a two-phaseapproach which in the first phase a new method for computing the importance weights of thesearch engines is introduced and in the second stage a minimax LP model for findingrelevant search engines results is formulated. To evaluate the retrieval effectiveness ofthe suggested method, the 50 queries of the 2002 TREC Web track were utilized andsubmitted to three popular Web search engines called Ask, Bing and Google. The returnedresults were aggregated using two exiting approaches, three high-performance commercialWeb metasearch engines and our proposed technique. The efficiency of the generated listswas measured using TREC-Style Average Precision (TSAP). The new findings demonstrate thatthe suggested model improved the quality of merging considerably.

In this paper, a batch arrival general bulk service queueing system with interruptedvacation (secondary job) is considered. At a service completion epoch, if the server findsat least ‘a’ customers waiting for service say ξ, heserves a batch of min (ξ, b) customers, whereb ≥ a. On the other hand, if the queue length is atthe most ‘a-1’, the server leaves for a secondary job (vacation) ofrandom length. It is assumed that the secondary job is interrupted abruptly and the serverresumes for primary service, if the queue size reaches ‘a’, during thesecondary job period. On completion of the secondary job, the server remains in the system(dormant period) until the queue length reaches ‘a’. For the proposedmodel, the probability generating function of the steady state queue size distribution atan arbitrary time is obtained. Various performance measures are derived. A cost model forthe queueing system is also developed. To optimize the cost, a numerical illustration isprovided.

The coupled tasks scheduling problem is a class of scheduling problems introduced forbeam steering software of sophisticated radar devices, called phased arrays. Due toincreasing popularity of such radars, the importance of coupled tasks scheduling isconstantly growing. Unfortunately, most of the coupled tasks problems are NP-hard, andonly a few practically usable algorithms for such problems were found. This paper providesa survey of already known complexity results of various variants of coupled tasksproblems. Then, it complements previous results by providing experimental results of twonew polynomial algorithms for coupled tasks scheduling, which are: an exact algorithm for1|(1,4,1),strictchains|Cmax problem,and a fast heuristic algorithm for more general1|(1,2k, 1), strictchains|Cmaxproblem, where k ∈ ℕ.

Consider an M/M/1 retrial queue with collisions and working vacation interruption underN-policy. We use a quasi birth and death process to describe the considered system andderive a condition for the stability of the model. Using the matrix-analytic method, weobtain the stationary probability distribution and some performance measures. Furthermore,we prove the conditional stochastic decomposition for the queue length in the orbit.Finally, some numerical examples are presented.

This paper aims at describing the way Flow machinery may be used in order to deal with Resource Constrained Project Scheduling Problems (RCPSP). In order to do it, it first introduces the Timed Flow Polyhedron related to a RCPSP instance. Next it states several structural results related to connectivity and to cut management. It keeps on with a description of the way this framework gives rise to a generic Insertion operator, which enables programmers to design greedy and local search algorithms. It ends with numerical experiments.