Sharif Digital Repository

Since there is no difference etween uplink and downlink subframes in the IEEE 802.16 mesh mode; both downlink and uplink traffics are transmitted within a single time frame. Hence, in most scheduling methods, only one scheduling algorithm is used for both uplink and downlink traffic. However, because of the different characteristics of uplink and downlink traffic, different scheduling methods should be used for each of the traffic types. In this paper, we focus on the mesh centralized scheduling of downlink flow in the data subframe. After comprehensive analysis of the characteristics of downlink traffic, we propose a new algorithm, called Traffic-Aware Scheduling (TAS). In this algorithm,... 

The NP-hard single machine sequence-dependent group scheduling problem with minimization of total weighted earliness and tardiness is investigated. An arc-time-indexed formulation is presented and a Lagrangian-based branch-and-bound algorithm is proposed. The Lagrangian relaxation of the arc-time-indexed formulation is solved as a shortest path problem. The results of an extensive computational study demonstrate the efficacy of the proposed algorithm and establish characteristics of some hard to solve instances  

Cross-docking is a new logistic technique that brings considerable benefits such as low inventory level, customer satisfaction, etc. To achieve these benefits, coordination between transportation facilities is quite important. This paper studies both inbound and outbound scheduling problem and assignment of products from inbound truck to outbound trucks in a cross-docking warehouse including multiple receiving and shipping dock doors. To do so, an MILP model is developed, which is NP-hard. Thus, a GA algorithm is developed and has been strengthened with two proposed neighborhood search to tackle the developed problem in medium and large size instances. Finally, numerical results of three... 

The job shop scheduling problem is a difficult combinatorial optimization problem. This paper presents a hybrid algorithm which combines global equilibrium search, path relinking and tabu search to solve the job shop scheduling problem. The proposed algorithm used biased random sampling to have a better covering of the solution space. In addition, a new version of N6 neighborhood is applied in a tabu search framework. In order to evaluate the algorithm, comprehensive tests are applied to it using various standard benchmark sets. Computational results confirm the effectiveness of the algorithm and its high speed. Besides, 19 new upper bounds among the unsolved problems are found  

The job shop scheduling problem with makespan criterion is valuable from both practical and theoretical points of view. This problem has been attacked by most of the well-known meta-heuristic algorithms. Among them, tabu search has emerged as the most effective approach. The proposed algorithm takes advantages of both N1 and N6 neighborhoods. N1 neighborhood is used as a path relinking procedure while N6 neighborhood with its guideposts is applied in a tabu search framework. In addition, a method is presented for updating the topological order, heads and tails in N6 neighborhood. The algorithm is tested on standard benchmark sets, outperformed all previous approaches (include i-TSAB) and... 

Renewable and nonrenewable resources are the most studied resource types in the field of resource-constrained project scheduling problems, however cumulative resources are another type of resources, widespread in practical cases that have been theoretically studied much less than the two aforementioned types. So in the current paper we study resource-constrained project scheduling problem subject to cumulative resources (RCPSP-Cu), focusing on development of exact algorithms for the problem. We customize three resource-constrained project scheduling problem (RCPSP) branch and bound algorithms of extension alternatives, minimal delaying alternatives and minimal forbidden sets for RCPSP-Cu. We... 

A Particle Swarm Optimization (PSO) algorithm for a Flow Shop Sequence Dependent Group Scheduling (FSDGS) problem, with minimization of total flow time as the criterion (Fmmls, Spuc, prmu 52 Q), is proposed in this research. An encoding scheme based on Ranked Order Value (ROV) is developed, which converts the continuous position value of particles in PSO to job and group permutations. A neighborhood search strategy, called Individual Enhancement (IE), is fused to enhance the search and to balance the exploration and exploitation. The performance of the algorithm is compared with the best available meta-heuristic algorithm in literature, i.e. the Ant Colony Optimization (ACO) algorithm, based... 

This paper studies simultaneous lot sizing and scheduling problem in a job shop environment over a finite number of periods. The machines are flexible such that the production manager is able to change their working speeds. Also, the production schedule of the items over machines should be in consistence with technological precedence relationships. The problem is formulated as an integer linear program. Then, a number of valid inequalities are developed based on the problem structures. The proposed valid inequalities are added to the problem formulation in a "cut and branch" manner to accelerate the search process by common solvers. Finally, performance of the valid inequalities is... 

Process variation has already emerged as a major concern in design of multi-processor system on chips (MPSoC). In recent years, there have been several attempts to bring variability awareness into the task scheduling process of embedded MPSoCs to improve performance yield. This study attempts to provide a comparative study of the current variation-aware design-time task and communication scheduling techniques that target embedded MPSoCs. To this end, the authors first use a sign-off variability modelling framework to accurately estimate the frequency distribution of MPSoC components. The task scheduling methods are then compared in terms of both the quality of the final solution and the... 

Task scheduling algorithms in grid environments strive to maximize the overall throughput of the grid. In order to maximize the throughput of the grid environments, the makespan of the grid tasks should be minimized. In this paper, a new task scheduling algorithm is proposed to assign tasks to the grid resources with goal of minimizing the total makespan of the tasks. The algorithm uses the genetic approach to find the suitable assignment within grid resources. The experimental results obtained from applying the proposed algorithm to schedule independent tasks within grid environments demonstrate the applicability of the algorithm in achieving schedules with comparatively lower makespan in... 

This paper deals with the resource-constrained project scheduling problem with flexible work profiles. In this problem, a project contains activities interrelated by finish-start-type precedence constraints with a time lag of zero. In many real-life projects, however, it often occurs that only one renewable bottleneck resource is available and that activities do not have, a fixed prespecified duration and associated resource requirement, but a total work content, which essentially indicates how much work has to be performed on them. Based on this work content, all feasible work profiles have to be specified for the activities, each characterized by a, fixed duration and a resource... 

The focus of this research is on the flexible flow shop sequence dependent group scheduling problem (FFSDGS) with minimization of makespan as the criterion (FFm|fmls, Splk|Cmax). Since the research problem is shown to be NP-hard, a meta-heuristic algorithms based on memetic algorithm is developed to efficiently solve the problem. The performance of the proposed algorithm is compared with the only available meta-heuristic algorithm in the literature, i.e., tabu search (TS). The comparison is performed based on paired t-test and the result shows that the memetic algorithm has a superior performance compared to the TS  

The NP-hard single machine sequence-dependent group scheduling problem with minimization of total weighted earliness and tardiness is investigated. An arc-time-indexed formulation is presented and a Lagrangian-based branch-and-bound algorithm is proposed. The Lagrangian relaxation of the arc-time-indexed formulation is solved as a shortest path problem. The results of an extensive computational study demonstrate the efficacy of the proposed algorithm and establish characteristics of some hard to solve instances  

We have developed a mathematical programming model for minimizing total flow time of the flow shop sequence dependent group scheduling (FSDGS) problem, typically classified as Fm|fmls, Splk, prmu|∑Cj. As the problem is shown to be strongly NP-hard, a tabu search (TS) algorithm as well as a hybrid ant colony optimization (HACO) algorithm have been developed to heuristically solve the problem. A lower bounding (LB) method based on the Branch-and-Price algorithm is also developed to evaluate the quality of the metaheuristic algorithms. In order to compare the performance of metaheuristic algorithms, random test problems, ranging in size from small, medium, to large are created and solved by... 

Considering the collection of all networks with independent set interference model, Shah, Tse, and Tsitsiklis showed that there exist scheduling algorithms with polynomial complexity and delay, only if the maximum independent set problem can be solved in polynomial time (equivalently, P=NP). In this paper, we extend this result to arbitrary collections of networks and present a clear-cut criterion for the existence of polynomial complexity and delay scheduling algorithms relative to a given collection of networks with arbitrary interference models, not confined to independent set interference or SINR models, and not necessarily encompassing all network topologies. This amounts to the... 

In this article, scheduling and rescheduling problems with increasing processing time and new job insertion are studied for reprocessing problems in the remanufacturing process. To handle the unpredictability of reprocessing time, an experience-based strategy is used. Rescheduling strategies are applied for considering the effect of increasing reprocessing time and the new subassembly insertion. To optimize the scheduling and rescheduling objective, a discrete harmony search (DHS) algorithm is proposed. To speed up the convergence rate, a local search method is designed. The DHS is applied to two real-life cases for minimizing the maximum completion time and the mean of earliness and... 

This paper studies a simultaneous weekly assignment and scheduling decisionmaking problem in operating theaters with elective patients. Because of limited recourses in hospitals, considering assignment and scheduling decisions simultaneously can help mangers exploit the available resources more efficiently and make the work-load uniformly distributed during the planning horizon. This procedure can significantly reduce hospital costs and increase satisfaction of patients and personnel. This paper formulates the mentioned problem as a Mixed Integer Linear Program (MILP) considering applicable assumptions like finite recovery beds and limitation of equipment. Since the problem is NP-hard, in... 

Outpatient appointment scheduling problems have recently gained increasing attention. This paper provides a comprehensive review of recent analytical and numerical optimization studies that present decision-support tools for designing and planning outpatient appointment systems (OASs). A structure for organizing the recent literature according to various criteria is provided, including a framework that classifies decisions at the strategic, tactical, and operational levels. The OAS literature is evaluated from four perspectives: problem settings, environmental factors, modeling approaches, and solution methods. In addition, research gaps and areas of opportunity for future research are... 

Diffusion of key schedule algorithm plays an important role in security of block ciphers. In this paper, we present a new approach to key schedule diffusion analysis by taking the advantages of graph theory modeling. This modeling can help to disclose the weaknesses of key schedules. In this line, the key schedule weaknesses of Twine-128 are shown and an improved key schedule is proposed. In order to make a fair comparison, some parameters are introduced to quantify the diffusion property of key schedule, and compare the results for Twine-128 with both key schedules. The results show that the new key schedule made Twine-128 stronger. Also for more reliability, the results of biclique attack... 

In this article, scheduling and rescheduling problems with increasing processing time and new job insertion are studied for reprocessing problems in the remanufacturing process. To handle the unpredictability of reprocessing time, an experience-based strategy is used. Rescheduling strategies are applied for considering the effect of increasing reprocessing time and the new subassembly insertion. To optimize the scheduling and rescheduling objective, a discrete harmony search (DHS) algorithm is proposed. To speed up the convergence rate, a local search method is designed. The DHS is applied to two real-life cases for minimizing the maximum completion time and the mean of earliness and...