Impinging jet cleaning of tank walls: Effect of jet length, wall curvature and related phenomena

The effect of jet length and wall curvature on the flow patterns generated by an impinging water jet were quantified and the effect on cleaning investigated in a brief study. The length of time taken to establish steady flow was characterised. Jet impingement on a flat vertical wall was investigated for jets of diameter 2–4mm for lengths, L, up to 1m. The amount of liquid lost to splatter was measured and found to be insensitive to L for short L (1.5dm3min−1). The cleaning of two viscoplastic model food soils was studied briefly: a hydrophobic petroleum jelly and Carbopol®, a water-soluble gel. The splatter correction was not able to account for all the differences observed in cleaning at different jet lengths. There was no appreciable effect of curvature on cleaning behaviour. Soaking of the Carbopol® increased its cleaning rate.Funding for MWLC from Newnham College, Cambridge, and a Commonwealth Scholarship for RKB are gratefully acknowledged, as is travel funding for DIW to attend the FCFP2018 conference from Jesus College, Cambridge. Authors TVA, NT, SAW and RLW were all MEng research project students

A new initialization procedure for the distributed estimation of distribution algorithms

Estimation of distribution algorithms (EDAs) are one of the most promising paradigms in today’s evolutionary computation. In this field, there has been an incipient activity in the so-called parallel estimation of distribution algorithms (pEDAs). One of these approaches is the distributed estimation of distribution algorithms (dEDAs). This paper introduces a new initialization mechanism for each of the populations of the islands based on the Voronoi cells. To analyze the results, a series of different experiments using the benchmark suite for the special session on Real-parameter Optimization of the IEEE CEC 2005 conference has been carried out. The results obtained suggest that the Voronoi initialization method considerably improves the performance obtained from a traditional uniform initialization

Pareto Optimal Matchings in Many-to-Many Markets with Ties

We consider Pareto-optimal matchings (POMs) in a many-to-many market of applicants and courses where applicants have preferences, which may include ties, over individual courses and lexicographic preferences over sets of courses. Since this is the most general setting examined so far in the literature, our work unifies and generalizes several known results. Specifically, we characterize POMs and introduce the \emph{Generalized Serial Dictatorship Mechanism with Ties (GSDT)} that effectively handles ties via properties of network flows. We show that GSDT can generate all POMs using different priority orderings over the applicants, but it satisfies truthfulness only for certain such orderings. This shortcoming is not specific to our mechanism; we show that any mechanism generating all POMs in our setting is prone to strategic manipulation. This is in contrast to the one-to-one case (with or without ties), for which truthful mechanisms generating all POMs do exist

Necessary and sufficient optimality conditions for scheduling unit time jobs on identical parallel machines

In this paper we characterize optimal schedules for scheduling problems with parallel machines and unit processing times by providing necessary and sufficient conditions of optimality. We show that the optimality conditions for parallel machine scheduling are equivalent to detecting negative cycles in a specially defined graph. For a range of the objective functions, we give an insight into the underlying structure of the graph and specify the simplest types of cycles involved in the optimality conditions. Using our results we demonstrate that the optimality check can be performed by faster algorithms in comparison with existing approaches based on sufficient conditions

Most vital segment barriers

We study continuous analogues of "vitality" for discrete network flows/paths, and consider problems related to placing segment barriers that have highest impact on a flow/path in a polygonal domain. This extends the graph-theoretic notion of "most vital arcs" for flows/paths to geometric environments. We give hardness results and efficient algorithms for various versions of the problem, (almost) completely separating hard and polynomially-solvable cases

Program trace optimization with constructive heuristics for combinatorial problems

This is the author accepted manuscript. The final version is available from Springer via the DOI in this record.EvoCOP: 19th European Conference on Evolutionary Computation in Combinatorial Optimisation, 24-26 April 2019, Leipzig, GermanyProgram Trace Optimisation (PTO), a highly general optimisation framework, is applied to a range of combinatorial optimisation (COP) problems. It effectively combines \smart" problem-specifi c constructive heuristics and problem-agnostic metaheuristic search, automatically and implicitly designing problem-appropriate search operators. A weakness is identifi ed in PTO's operators when applied in conjunction with smart heuristics on COP problems, and an improved method is introduced to address this. To facilitate the comparison of this new method with the original, across problems, a common format for PTO heuristics (known as generators) is demonstrated, mimicking GRASP. This also facilitates comparison of the degree of greediness (the GRASP alpha parameter) in the heuristics. Experiments across problems show that the novel operators consistently outperform the original without any loss of generality or cost in CPU time; hill-climbing is a sufficient metaheuristic; and intermediate levels of greediness are usually best

A scheme for determining vehicle routes based on Arc-based service network design

In freight transportation, less-than-truckload carriers often need to assign each vehicle a cyclic route so that drivers can come back home after a certain period of time. However, the Node-Arc model for service network design addresses decisions on each arc and does not determine routes directly, although the vehicle balancing constraint ensures that the number of outgoing vehicles equals the number of incoming vehicles at each node. How to transform the optimized service network into a set of vehicle routes remains an important problem that has not yet been studied. In this paper, we propose a three-phase scheme to address this problem. In the first stage, we present an algorithm based on the depth-first search to find all of the different cyclic routes in a service network design solution. In the second stage, we propose to prune poor cyclic routes using real-life constraints so that a collection of acceptable vehicle routes can be obtained before route assignment. Some of the pruning can also be done in the first stage to speed up the proposed algorithm. In the third stage, we formulate the problem of selecting a set of cyclic routes to cover the entire network as a weighted set covering problem. The resulting model is formulated as an integer program and solved with IBM ILOG CPLEX solver. Experimental results on benchmark instances for service network design indicate the effectiveness of the proposed scheme which gives high-quality solutions in an efficient way

Machine speed scaling by adapting methods for convex optimization with submodular constraints

In this paper, we propose a new methodology for the speed-scaling problem based on its link to scheduling with controllable processing times and submodular optimization. It results in faster algorithms for traditional speed-scaling models, characterized by a common speed/energy function. Additionally, it efficiently handles the most general models with job-dependent speed/energy functions with single and multiple machines. To the best of our knowledge, this has not been addressed prior to this study. In particular, the general version of the single-machine case is solvable by the new technique in O(n2) time

Conjunctions of Among Constraints

Many existing global constraints can be encoded as a conjunction of among constraints. An among constraint holds if the number of the variables in its scope whose value belongs to a prespecified set, which we call its range, is within some given bounds. It is known that domain filtering algorithms can benefit from reasoning about the interaction of among constraints so that values can be filtered out taking into consideration several among constraints simultaneously. The present pa- per embarks into a systematic investigation on the circumstances under which it is possible to obtain efficient and complete domain filtering algorithms for conjunctions of among constraints. We start by observing that restrictions on both the scope and the range of the among constraints are necessary to obtain meaningful results. Then, we derive a domain flow-based filtering algorithm and present several applications. In particular, it is shown that the algorithm unifies and generalizes several previous existing results.Comment: 15 pages plus appendi