Concurrent Programming Techniques

2017 ◽  
pp. 105-136
Author(s):  
Ivan Cibrario Bertolotti ◽  
Tingting Hu
Keyword(s):  
Concurrent Programming ◽  
Programming Techniques

scholarly journals Digital telephone switch: Software

2003 ◽  
Vol 1 (02) ◽  
Author(s):  
J. G. Viveros Talavera ◽  
J. P. Abarca Reyna ◽  
E. Noriega Solano
Keyword(s):  
Object Oriented ◽  
Control Program ◽  
Concurrent Programming ◽  
Object Oriented Programming ◽  
Maximum Capacity ◽  
Programming Techniques

This paper describes the design of the program of control for a Digital Phone Switch (PBAX) with a maximum capacity of one hundred and twenty-eight lines (extensions and trunks). The control program was designed using object-oriented programming and concurrent programming techniques.

Robust Benchmarking of Indian Mutual Funds-A Partial Frontier Approach

2015 ◽  
Vol 5 (2) ◽  
Author(s):  
Ram Pratap Sinha
Keyword(s):  
Decision Making ◽  
Performance Evaluation ◽  
Mutual Funds ◽  
Mutual Fund ◽  
Multi Criteria Decision Making ◽  
Risk Framework ◽  
Programming Techniques ◽  
Risk Free Rate ◽  
Risk Ratios ◽  
Free Rate

Performance analysis of mutual funds is usually made on the basis of return-risk framework. Traditionally, excess return (over risk-free rate) to risk ratios were used for the purpose mutual fund evaluation. Subsequently, the application of non-parametric mathematical programming techniques in the context of performance evaluation facilitated multi-criteria decision making. However,the estimates of performance on the basis of conventional programming techniques like DEA and FDH are affected by the presence of outliers in the sample observations. The present, accordingly uses more robust benchmarking techniques for evaluating the performance od sectoral mutual fund schemes based on observations for the second half of 2010. The USP of the present study is that it uses two partial frontier techniques (Order-m and Order- a) which are less susceptible to the problem of extreme data.

scholarly journals A Hybrid Methodology to Minimize Freshwater Consumption during Shrimp Shell Waste Valorization Combining Multi-Contaminant Pinch Analysis and Superstructure Optimization

Polymers ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1887
Author(s):  
Viviana Quintero ◽  
Arturo Gonzalez-Quiroga ◽  
Angel Darío Gonzalez-Delgado
Keyword(s):  
Process Integration ◽  
Preliminary Design ◽  
Water Network ◽  
Hybrid Strategy ◽  
Shrimp Shell ◽  
Optimal Value ◽  
Shell Waste ◽  
Programming Techniques ◽  
Shrimp Shell Waste ◽  
Freshwater Consumption

The conservation and proper management of natural resources constitute one of the main objectives of the 2030 Agenda for Sustainable Development designed by the Member States of the United Nations. In this work, a hybrid strategy based on process integration is proposed to minimize freshwater consumption while reusing wastewater. As a novelty, the strategy included a heuristic approach for identifying the minimum consumption of freshwater with a preliminary design of the water network, considering the concept of reuse and multiple pollutants. Then, mathematical programming techniques were applied to evaluate the possibilities of regeneration of the source streams through the inclusion of intercept units and establish the optimal design of the network. This strategy was used in the shrimp shell waste process to obtain chitosan, where a minimum freshwater consumption of 277 t/h was identified, with a reuse strategy and an optimal value of US $5.5 million for the design of the water network.

Causal-Consistent Replay Reversible Semantics for Message Passing Concurrent Programs

2021 ◽  
Vol 178 (3) ◽  
pp. 229-266
Author(s):  
Ivan Lanese ◽  
Adrián Palacios ◽  
Germán Vidal
Keyword(s):  
Programming Language ◽  
Message Passing ◽  
Concurrent Programming ◽  
Concurrent Systems ◽  
Concurrent Programs ◽  
Unified Framework ◽  
Innovative Technique ◽  
Dual Notion

Causal-consistent reversible debugging is an innovative technique for debugging concurrent systems. It allows one to go back in the execution focusing on the actions that most likely caused a visible misbehavior. When such an action is selected, the debugger undoes it, including all and only its consequences. This operation is called a causal-consistent rollback. In this way, the user can avoid being distracted by the actions of other, unrelated processes. In this work, we introduce its dual notion: causal-consistent replay. We allow the user to record an execution of a running program and, in contrast to traditional replay debuggers, to reproduce a visible misbehavior inside the debugger including all and only its causes. Furthermore, we present a unified framework that combines both causal-consistent replay and causal-consistent rollback. Although most of the ideas that we present are rather general, we focus on a popular functional and concurrent programming language based on message passing: Erlang.

scholarly journals An analytics-based heuristic decomposition of a bilevel multiple-follower cutting stock problem

OR Spectrum ◽  
2021 ◽  
Author(s):  
Adejuyigbe O. Fajemisin ◽  
Laura Climent ◽  
Steven D. Prestwich
Keyword(s):  
Real Life ◽  
Forest Harvesting ◽  
Cutting Stock Problem ◽  
Cutting Stock ◽  
Decomposition Approach ◽  
New Class ◽  
Bilevel Problem ◽  
Programming Techniques ◽  
Bilevel Problems ◽  
Better Than

AbstractThis paper presents a new class of multiple-follower bilevel problems and a heuristic approach to solving them. In this new class of problems, the followers may be nonlinear, do not share constraints or variables, and are at most weakly constrained. This allows the leader variables to be partitioned among the followers. We show that current approaches for solving multiple-follower problems are unsuitable for our new class of problems and instead we propose a novel analytics-based heuristic decomposition approach. This approach uses Monte Carlo simulation and k-medoids clustering to reduce the bilevel problem to a single level, which can then be solved using integer programming techniques. The examples presented show that our approach produces better solutions and scales up better than the other approaches in the literature. Furthermore, for large problems, we combine our approach with the use of self-organising maps in place of k-medoids clustering, which significantly reduces the clustering times. Finally, we apply our approach to a real-life cutting stock problem. Here a forest harvesting problem is reformulated as a multiple-follower bilevel problem and solved using our approach.

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