Scheduling

Contention-aware node allocation policy for high-performance capacity systems

by Ana Jokanovic

In ACM 6th Workshop on Interconnection Network Architectures: On-Chip, Multi-Chip (INA-OCMC), Paris (France), Jan 2012.

GridMAP-A Solution for Monitoring, Analysing and Predicting Network Performance and Resource Availability in Grids

by Yehia El-khatib

Providing grid schedulers with passive network measurements

by Yehia El-khatib

DATA MINING BASED DISCOVERY OF DISPATCHING RULES FOR JOB SHOP SCHEDULING PROBLEMS

by Atif SHAHZAD

Alternative solution representations for the job shop scheduling problem in ant colony optimisation (2007)

by James Montgomery

3rd Australian Conference on Artificial Life
http://dx.doi.org/10.1007/978-3-540-76931-6_1

Minimizing cycle time in single machine scheduling with start time-dependent processing times

by Mehdi Hosseinabadi Farahani

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
2012, DOI: 10.1007/s00170-012-4116-1

This paper considers the single machine scheduling problem with a new version of time-dependent processing times. The... more This paper considers the single machine scheduling problem with a new version of time-dependent processing times. The processing time of a job is defined as a piecewise linear function of its start time. It is preferred that the processing of each job be started at a specific time which means that processing the job before or after that time implies additional effort to accomplish the job. The job-processing time is a nonmonotonic function of its start time. The increasing rate of processing times is job independent and the objective is to minimize the cycle time. We show that the optimal schedule is V shaped and propose an optimal polynomial time algorithm for the problem.

Optimizing Point-to-Multipoint Transmissions in High Speed Packet Access Networks

by Giuseppe Araniti

Co-authored with: V. Scordamaglia, A. Molinaro, A. Iera, G. Interdonato, and F. Spanò; Published in IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB'11), 8-10 June 2011, Metropolitan Area Nuremberg, Germany. ISBN: 9781612841212

In this paper an innovative Radio Resource Management (RRM) algorithm is proposed with the purpose of increasing High... more In this paper an innovative Radio Resource Management (RRM) algorithm is proposed with the purpose of increasing High Speed Packet Access (HSPA) performances, in terms of system capacity and service quality, when the Multimedia Broadcast Multicast Services (MBMS) is supplied. The proposed RRM algorithm exploits channel quality indications to set up point-to-multipoint connections to subgroups of multicast users and to select the proper modulation and coding schemes on the downlink. The number of subgroups is determined through an optimization technique that also takes into account the
user satisfaction. An exhaustive simulation campaign is conducted to compare the proposed algorithm with the most promising approaches in the literature. Comparisons aim to assess the capability of the proposed RRM algorithm to efficiently manage group oriented services by providing an increment in terms of user satisfaction.

A new temporal csp framework handling composite variables and activity constraints

by Malek Mouhoub

M. Mouhoub and A. Sukpan. A New Temporal CSP Framework Handling Composite Variables and Activity Constraints. The 17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05), pages 143-149, Hong Kong, November 14-16, 2005

A well known approach to managing the numeric and the symbolic aspects of time is to view them as Constraint... more A well known approach to managing the numeric and the symbolic aspects of time is to view them as Constraint Satisfaction Problems (CSPs). Our aim is to extend the temporal CSP formalism in order to include activity constraints and composite variables. Indeed, in many real life applications the set of variables involved by the temporal constraint problem to solve is not known in advance. More precisely, while some temporal variables (called events) are available in the initial problem, others are added dynamically to the problem during the resolution process via activity constraints and composite variables. Activity constraints allow some variables to be activated (added to the problem) when activity conditions are true. Composite variables are defined on finite domains of events. We propose in this paper two methods based respectively on constraint propagation and stochastic local search (SLS) for solving temporal constraint problems with activity constraints and composite variables. We call these problems Conditional and Composite Temporal Constraint Satisfaction Problems (CCTCSPs). Experimental study we conducted on randomly generated CCTCSPs demonstrates the efficiency of our exact method based on constraint propagation in the case of middle constrained and over constrained problems while the SLS based method is the technique of choice for under constrained problems and also in case we want to trade search time for the quality of the solution returned (number of solved constraints).

Reasoning with numeric and symbolic time information

by Malek Mouhoub

M. Mouhoub. Reasoning with numeric and symbolic time information. Artificial Intelligence Review. Kluwer Academic Publishers. Vol. 21, pages 25-56, 2004.

Representing and reasoning about time is fundamental in many applications of Artificial Intelligence as well as of... more Representing and reasoning about time is fundamental in many applications of Artificial Intelligence as well as of other disciplines in computer science, such as scheduling, planning, computational linguistics, database design and molecular biology. The development of a domain-independent temporal reasoning system is then practically important. An important issue when designing such systems is the efficient handling of qualitative and metric time information. We have developed a temporal model, TemPro, based on the Allen interval algebra, to express and manage such information in terms of qualitative and quantitative temporal constraints. TemPro translates an application involving temporal information into a Constraint Satisfaction Problem (CSP). Constraint satisfaction techniques are then used to manage the different time information by solving the CSP. In order for the system to deal with real time applications or those applications where it is impossible or impractical to solve these problems completely, we have studied different methods capable of trading search time for solution quality when solving the temporal CSP. These methods are exact and approximation algorithms based respectively on constraint satisfaction techniques and local search. Experimental tests were performed on randomly generated temporal constraint problems as well as on scheduling problems in order to compare and evaluate the performance of the different methods we propose. The results demonstrate the efficiency of the MCRW approximation method to deal with under constrained and middle constrained problems while Tabu Search and SDRW are the methods of choice for over constrained problems.

Experimental analysis of numeric and symbolic constraint satisfaction techniques for temporal reasoning

by Malek Mouhoub

M. Mouhoub, F. Charpillet and J.P. Haton. Experimental Analysis of Numeric and Symbolic Constraint Satisfaction Techniques for Temporal Reasoning. Constraints: An International Journal, Vol. 2, pages 151-164, Kluwer Academic Publishers, June 1998.

Many temporal applications like planning and scheduling can be viewed as special cases of numeric and symbolic... more Many temporal applications like planning and scheduling can be viewed as special cases of numeric and symbolic temporal constraint satisfaction problem. We have developed a temporal model, TemPro, based on the interval algebra, to express such applications in terms of qualitative and quantitative temporal constraints. TemProextends the interval algebra relations of Allen to handle numericinformation. To solve a constraint satisfaction problem, different approaches have been developed. These approaches generally use constraint propagation to simplify the original problem, and backtracking to directly search for possible solutions. Constraint propagation can also be used during backtracking to improve the performance of the search. The objectiveof this paper is to assess different policies for checking if aTemPro network is consistent. The main question we want to answer is how much constraint propagation is useful forfinding a single solution for a TemPro constraint graph. For this purpose, we have randomly generated large consistent networks for which arc and/or path consistency algorithms (AC-3, AC-7 and PC-2) were applied. The main result of this study is an optimal policy combining these algorithms either at the symbolic (Allen relation propagation) or at the numerical level.

Analysis of Approximation Algorithms for Maximal Temporal Constraint Satisfaction Problems

by Malek Mouhoub

M. Mouhoub. Analysis of Approximation Algorithms for Maximal Temporal Constraint Satisfaction Problems. The 2001 International Conference on Artificial Intelligence(IC-AI'2001), pages 165-171, Las Vegas, 2001.

This paper presents an experimental study of the different local
search techniques to solve Maximal Temporal... more This paper presents an experimental study of the different local
search techniques to solve Maximal Temporal Constraint Satisfaction Problems. Comparisons were carried out using Min-Conflicts-Random-Walk, Steepest-Descent-Random-Walk and Tabu Search methods. Empirical evidence shows that the Min-Conflicts-Random-Walk method finds almost always solutions of better quality, i.e solutions having smaller number of violated constraints and is faster than the other approximation methods to find solutions of the same quality.

Conditional and composite temporal CSPs

by Malek Mouhoub

M. Mouhoub and A. Sukpan. Conditional and Composite Temporal CSPs. Applied Intelligence, Vol. 36(1), pages 90-107 Springer, 2012

Constraint Satisfaction Problems (CSPs) have been widely used to solve combinatorial problems. In order to deal with... more Constraint Satisfaction Problems (CSPs) have been widely used to solve combinatorial problems. In order to deal with dynamic CSPs where the information regarding any possible change is known a priori and can thus be enumerated beforehand, conditional constraints and composite variables have been studied in the past decade. Indeed, these two concepts allow the addition of variables and their related constraints in a dynamic manner during the resolution process. More precisely, a conditional constraint restricts the participation of a variable in a feasible scenario while a composite variable allows us to express a disjunction of variables where only one will be added to the problem to solve. In order to deal with a wide variety of real life applications under temporal constraints, we present in this paper a unique temporal CSP framework including numeric
and symbolic temporal information, conditional constraints and composite variables. We call this model, a Conditional and Composite Temporal CSP (or CCTCSP). To solve the CCTCSP we propose two methods respectively based on Stochastic Local Search (SLS) and constraint propagation. In order to assess the efficiency in time of the solving methods we propose, experimental tests have been conducted on randomly generated CCTCSPs. The results demonstrate the superiority of a variant of the Maintaining Arc Consistency (MAC) technique (that we call MAX+) over the other constraint propagation strategies, Forward Checking (FC) and its variants, for both consistent and inconsistent problems. It has also been shown that, in the case of consistent problems, MAC+ outperforms the SLS method Min Conflict Random Walk (MCRW) for highly constrained CCTCSPs
while both methods have comparable time performance for under and middle constrained problems. MCRW is, however, the method of choice for highly constrained CCTCSPs if we decide to trade search time for the quality of the solution returned (number of solved constraints).

Multi-objective genetic algorithm for cell formation problem considering cellular layout and operations scheduling

by Mehdi Hosseinabadi Farahani

International Journal of Computer Integrated Manufacturing
DOI:10.1080/0951192X.2012.665182

Integrated design of cellular manufacturing (CM) systems consist of three major decisions: cell formation (CF),... more Integrated design of cellular manufacturing (CM) systems consist of three major decisions: cell formation (CF), cellular layout (CL) and planning issues such as cellular scheduling (CS). This article presents a mathematical model to concurrently identify the formation of cells, cellular layout and the operations sequence with the objective of minimising total transportation cost of parts as well as minimising makespan. A multi-objective genetic algorithm (MOGA) is then developed to solve the problem. The proposed MOGA exploits a novel evolutionary process which enables it to efficiently find Pareto optimal solutions. Computational results show the advantages of the proposed integrated approach and the superiority of the proposed MOGA over some well-known multi-objective evolutionary algorithms.

Energy-Aware Scheduling of Distributed Systems Using Cellular Automata

by Shrisha Rao

6th Annual IEEE International Systems Conference (IEEE SysCon 2012), Vancouver, Canada, March 2012.

In today’s world of large distributed systems, the need for energy efficiency of individual components is comple-... more In today’s world of large distributed systems, the need for energy efficiency of individual components is comple- mented by the need for energy awareness of the complete system. Hence, energy-aware scheduling of tasks on systems has become very important. Our work addresses the problem of finding an energy-aware schedule for a given system which also satisfies the precedence constraints between tasks to be performed by the system. We present a method which uses cellular automata to find a near-optimal schedule for the system. The rules for cellular automata are learned using a genetic algorithm. Though the work presented in this paper is not limited to scheduling in computing environments only, the work is validated with a sample simulation on distributed computing systems, and tested with some standard program graphs.

A MATRIX ALGORITHM RUPSP / GRUPSP “NO SPLITTING ALLOWED” FOR PRODUCTION PLANNING UNDER LEAN CONSTRUCTION METHODOLOGY BASED ON PRODUCTION PROCESSES

by José Luis Ponz Tienda

Ponz-Tienda. José Luis
Benlloch Marco. J.
Andrés Romano. C.
Doria Gil Senabre

Revista de la Construcción
Volumen 10 Nº 2-2011 paginas 90-103
ISSN 0717-7925 ISSN electrónico 0718-915x

Production Planning and Scheduling in the field of construction may be the great pending construction scheduling... more Production Planning and Scheduling in the field of construction may be the great pending construction scheduling subject, and one of the major objectives of the Lean Construction methodology.
In this article, is intended to clarify the limitations of the calculation algorithms used, and offer a new algorithm for programming projects in Lean Construction environments through graphs PDM (Diagramming Method Precedence) without interruption (not splitting allowed) and generalized precedence relations (GPR´s) based on constructive processes for the correct application of scheduling, optimization and production control models.
Keywords: Lean Construction, Construction scheduling, project scheduling, PDM, RUPSP, GRUPSP, RCPSP, GRCPSP, Production Planning, no splitting allowed

An Empirical Analysis of Heuristics for Solving the Two-Machine Flow Shop Problem with Job Release Times

by Pawel Kalczynski

Kalczynski, P.; Kamburowski, J, (in press) "An Empirical Analysis of Heuristics for Solving the Two-Machine Flow Shop Problem with Job Release Times" Computers and Operations Research

The theoretical analysis of heuristics for solving intractable optimization problems has many well-known drawbacks.... more The theoretical analysis of heuristics for solving intractable optimization problems has many well-known drawbacks. Constructed instances demonstrating an exceptionally poor worst-case performance of heuristics are typically too peculiar to occur in practice. Theoretical results on the average-case performance of most heuristics could not be established due to the difficulty with the use of probabilistic analysis. Moreover, the heuristics for which some type of asymptotic optimality has been proven are likely to perform questionably in practice. The purpose of this paper is to confront known theoretical results with our empirical results concerning heuristics for solving the strongly NP-hard problem of minimizing the makespan in a two-machine flow shop with job release times. The heuristics’ performance is examined with respect to their average and maximum relative errors, as well as their optimality rate, that is, the probability of being optimal. In particular, this allows us to observe that the asymptotic optimality rate of so called “almost surely asymptotically optimal” heuristic can be zero. We also present a new heuristic with theoretically short worst-case running time and statistically prove that it outperforms all heuristics known so far. However, our empirical experiments reveal that the heuristic is on average slower that its competitors with much longer worst-case running times.

Platoon-based self-scheduling for real-time traffic signal control

by Xiao-Feng Xie

Complete fuzzy scheduling and fuzzy earned value management in construction projects.

by Víctor Yepes

PONZ-TIENDA, J.L.; PELLICER, E.; YEPES, V. (2012). Complete fuzzy scheduling and fuzzy earned value management in construction projects. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering, 13(1):56-68. DOI:10.1631/jzus.A1100160. ISSN 1673-565X (Print); ISSN 1862-1775 (Online).

This paper aims to present a comprehensive proposal for project scheduling and control by applying fuzzy earned value.... more This paper aims to present a comprehensive proposal for project scheduling and control by applying fuzzy earned value. It goes a step further than the existing literature: in the formulation of the fuzzy earned value we consider not only its duration, but also cost and production, and alternatives in the scheduling between the earliest and latest times. The mathematical model is  mplemented in a prototypical construction project with all the estimated values taken as fuzzy numbers. Our findings suggest that different possible schedules and the fuzzy arithmetic provide more objective results in uncertain environments than
the traditional methodology. The proposed model allows for controlling the vagueness of the environment through the adjustment of the α-cut, adapting it to the specific circumstances of the project.

A novel hybrid genetic algorithm for the open shop scheduling problem

by Mehdi Hosseinabadi Farahani

International Journal of Advanced Manufacturing Technology
DOI 10.1007/s00170-011-3825-1

In this paper, a hybrid genetic algorithm is proposed for the open shop scheduling problem with the objective of... more In this paper, a hybrid genetic algorithm is proposed for the open shop scheduling problem with the objective of minimizing the makespan. In the proposed algorithm, a specialized crossover operator is used that preserves the relative order of jobs on machines and a strategy is applied to prevent from searching redundant solutions in the mutation operator. Moreover, an iterative optimization heuristic is employed which uses the concept of randomized active schedules, a dispatching index based on the longest remaining processing time rule and a lower bound to further decrease the search space. Computational results show that the proposed algorithm outperforms other genetic algorithms and is very competitive with well-known metaheuristics available in the literature.

Operating cost aware scheduling model for distributed servers based on global power pricing policies

by Shrisha Rao

Co-authored with Sudha Mani. Compute 2011: The 4th ACM Bangalore Conference, Bangalore, March 2011. doi:10.1145/1980422.1980434.

Reducing the power consumption and operational cost of IT servers is of great concern today. With the growth of the... more Reducing the power consumption and operational cost of IT servers is of great concern today. With the growth of the Internet and online services, the number of data centers is increasing day by day. Servers for many cloud applications and other large providers are spread globally. Energy costs across the globe vary dynamically. Servers operate at varied energy costs based on their location and time of use. The load of a server varies based on its geographical location and the time of operation. This paper focuses on exploiting the dynamic nature of electrical power pricing, so that a cost saving is obtained by geo-location of requests to servers operating at lower costs at particular times. There exist patterns of load that are similar for different types of servers. Scheduling decisions are made considering both loads and operating costs of the servers into account, i.e., requests are scheduled to run on servers operating at low cost that also have low expected load. In order to meet the business requirements of an application, scheduling decisions for requests that have stringent SLA considerations or high server affinity, are made by assigning high priority for these requests. Geo-location of requests is done for low priority requests.