Search results for: parallel job shop scheduling problem

Authors: Norhayati Mohd Rasip, Abd. Samad Hasan Basari , Nuzulha Khilwani Ibrahim, Burairah Hussin

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The allocation of working schedule especially for shift environment is hard to fulfill its fairness among them. In the case of nurse scheduling, to set up the working time table for them is time consuming and complicated, which consider many factors including rules, regulation and human factor. The scenario is more complicated since most nurses are women which have personnel constraints and maternity leave factors. The undesirable schedule can affect the nurse productivity, social life and the absenteeism can significantly as well affect patient's life. This paper aimed to enhance the scheduling process by utilizing the particle swarm optimization in order to solve nurse scheduling problem. The result shows that the generated multiple initial schedule is fulfilled the requirements and produces the lowest cost of constraint violation.

Keywords: nurse scheduling, particle swarm optimisation, nurse rostering, hard and soft constraint

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Authors: Max Moleke, Gilbert Mbonde

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Coordinating supply chain process within a manufacturing environment is a very critical aspect of any organization. Nowadays, most manufacturing industries turn to look at only the financial indicator which in real life situation on the shop floor, there are a number of supply chain disruptions that are been ignored. In this work, we had to look at different types of supply chain disruption and their various impact within the organization. A number of Industrial engineering tools are employed which includes, Multifactor productivity, activity on arrow and rescheduling plans. The final result shows that supply chain disruption various with different geographical area where the production plant is operating.

Keywords: supply chain, disruptions, flow shop scheduling, uncertainty

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Authors: Martha Ndeley, John Ikome

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In this paper, we expand the scope of constraint-directed techniques to deal with the case of transportation schedule with capacity restrictions where the scheduling problem includes alternative activities. That is, not only does the scheduling problem consist of determining when an activity is to be executed, but also determining which set of alternative activities is to be executed at all level of transportation from input to output. Such problems encompass both alternative resource problems and alternative process plan problems. We formulate a constraint-based representation of alternative activities to model problems containing such choices. We then extend existing constraint-directed scheduling heuristic commitment techniques and propagators to reason directly about the fact that an activity does not necessarily have to exist in a final transportation schedule without being completed. Tentative results show that an algorithm using a novel texture-based heuristic commitment technique propagators achieves the best overall performance of the techniques tested.

Keywords: production, transportation, scheduling, integrated

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Authors: Ali Allahverdi, Harun Aydilek, Asiye Aydilek

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The two stage assembly flowshop scheduling problem has lots of application in real life. To the best of our knowledge, the two stage assembly flowshop scheduling problem with total tardiness performance measure and separate setup times has not been addressed so far, and hence, it is addressed in this paper. Different dominance relations are developed and several algorithms are proposed. Extensive computational experiments are conducted to evaluate the proposed algorithms. The computational experiments have shown that one of the algorithms performs much better than the others. Moreover, the experiments have shown that the best performing algorithm performs much better than the best existing algorithm for the case of zero setup times in the literature. Therefore, the proposed best performing algorithm not only can be used for problems with separate setup times but also for the case of zero setup times.

Keywords: scheduling, assembly flowshop, total tardiness, algorithm

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Authors: M. Benbouzid, Q. Bresson, A. Duclos, K. Longo, Q. Morel

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Currently, electricity suppliers must predict the consumption of their customers in order to deduce the power they need to produce. It is, then, important in a first step to optimize household consumption to obtain more constant curves by limiting peaks in energy consumption. Here centralized real time scheduling is proposed to manage the equipment's starting in parallel. The aim is not to exceed a certain limit while optimizing the power consumption across a habitat. The Raspberry Pi is used as a box; this scheduler interacts with the various sensors in 6LoWPAN. At the scale of a single dwelling, household consumption decreases, particularly at times corresponding to the peaks. However, it would be wiser to consider the use of a residential complex so that the result would be more significant. So, the ceiling would no longer be fixed. The scheduling would be done on two scales, firstly, per dwelling, and secondly, at the level of a residential complex.

Keywords: smart grid, energy box, scheduling, Gang Model, energy consumption, energy management system, wireless sensor network

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Authors: Ismail El Gayar, Ossama Ismail, Yousri El Gamal

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This paper presented a technique to solve one of the transportation problems that faces us in real life which is the Bus Scheduling Problem. Most of the countries using buses in schools, companies and traveling offices as an example to transfer multiple passengers from many places to specific place and vice versa. This transferring process can cost time and money, so we build a decision support system that can solve this problem. In this paper, a genetic algorithm with the shortest path technique is used to generate a competitive solution to other well-known techniques. It also presents a comparison between our solution and other solutions for this problem.

Keywords: bus scheduling problem, decision support system, genetic algorithm, shortest path

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Authors: Wook-Won Kim, Je-Seok Shin, Jin-O Kim

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This paper propose the method for optimal scheduling for battery energy storage system with reliability constraint of energy storage system in reliability aspect. The optimal scheduling problem is solved by dynamic programming with proposed transition matrix. Proposed optimal scheduling method guarantees the minimum fuel cost within specific reliability constraint. For evaluating proposed method, the timely capacity outage probability table (COPT) is used that is calculated by convolution of probability mass function of each generator. This study shows the result of optimal schedule of energy storage system.

Keywords: energy storage system (ESS), optimal scheduling, dynamic programming, reliability constraints

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Authors: Masoumeh Ali Pouri, Hamid Haj Seyyed Javadi

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Nowadays, cloud processing is one of the important issues in information technology. Since scheduling of tasks graph is an NP-hard problem, considering approaches based on undeterminisitic methods such as evolutionary processing, mostly genetic and cuckoo algorithms, will be effective. Therefore, an efficient algorithm has been proposed for scheduling of tasks graph to obtain an appropriate scheduling with minimum time. In this algorithm, the new approach is based on making the length of the critical path shorter and reducing the cost of communication. Finally, the results obtained from the implementation of the presented method show that this algorithm acts the same as other algorithms when it faces graphs without communication cost. It performs quicker and better than some algorithms like DSC and MCP algorithms when it faces the graphs involving communication cost.

Keywords: cloud computing, scheduling, tasks graph, chakoos algorithm

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Authors: Didem Can

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Scheduling problems are one of the most fundamental issues of production systems. Many different approaches and models have been developed according to the production processes of the parts and the main purpose of the problem. In this study, one of the bottleneck stations of a company serving in the aerospace industry is analyzed and considered as a single machine scheduling problem with sequence-dependent setup times. The objective of the problem is assigning a large number of similar parts to the same shift -to reduce chemical waste- while minimizing the number of tardy jobs. The goal programming method will be used to achieve two different objectives simultaneously. The assignment of parts to the shift will be expressed using the integer programming method. Finally, the constraint programming method will be used as it provides a way to find a result in a short time by avoiding worse resulting feasible solutions with the defined variables set. The model to be established will be tested and evaluated with real data in the application part.

Keywords: constraint programming, goal programming, integer programming, sequence-dependent setup, single machine scheduling

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Authors: Parampal Kaur, Deepak Aggarwal

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In the computational Grid, fault tolerance is an imperative issue to be considered during job scheduling. Due to the widespread use of resources, systems are highly prone to errors and failures. Hence, fault tolerance plays a key role in the grid to avoid the problem of unreliability. Scheduling the task to the appropriate resource is a vital requirement in computational Grid. The fittest resource scheduling algorithm searches for the appropriate resource based on the job requirements, in contrary to the general scheduling algorithms where jobs are scheduled to the resources with best performance factor. The proposed method is to improve the fault tolerance of the fittest resource scheduling algorithm by scheduling the job in coordination with job replication when the resource has low reliability. Based on the reliability index of the resource, the resource is identified as critical. The tasks are scheduled based on the criticality of the resources. Results show that the execution time of the tasks is comparatively reduced with the proposed algorithm using real-time approach rather than a simulator.

Keywords: computational grid, fault tolerance, task replication, job scheduling

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Authors: E. Koyuncu

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The problem of Order Acceptance and Scheduling (OAS) is defined as a joint decision of which orders to accept for processing and how to schedule them. Any linear programming model representing real-world situation involves the parameters defined by the decision maker in an uncertain way or by means of language statement. Fuzzy data can be used to incorporate vagueness in the real-life situation. In this study, a fuzzy mathematical model is proposed for a single machine OAS problem, where the orders are defined by their fuzzy due dates, fuzzy processing times, and fuzzy sequence dependent setup times. The signed distance method, one of the fuzzy ranking methods, is used to handle the fuzzy constraints in the model.

Keywords: fuzzy mathematical programming, fuzzy ranking, order acceptance, single machine scheduling

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Authors: Jian Zheng, Yoshiyasu Takahashi, Yuichi Kobayashi, Tatsuhiro Sato

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In the study, we present a conceptual framework for developing a scheduling system that can generate self-explanatory and easy-understanding schedules. To this end, a user interface is conceived to help planners record factors that are considered crucial in scheduling, as well as internal and external sources relating to such factors. A hybrid approach combining machine learning and constraint programming is developed to generate schedules and the corresponding factors, and accordingly display them on the user interface. Effects of the proposed system on scheduling are discussed, and it is expected that scheduling efficiency and system understandability will be improved, compared with previous scheduling systems.

Keywords: constraint programming, factors considered in scheduling, machine learning, scheduling system

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Authors: Sapan Tiwari, Namrata Ghosh

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In urban mass transit, crew scheduling always plays a significant role. It deals with the formulation of work timetables for its staff so that an organization can meet the demand for its products or services. The efficient schedules of a specified timetable have an enormous impact on staff demand. It implies that an urban mass transit company's financial outcomes are strongly associated with planning operations in the region. The research aims to demonstrate the state of the crew scheduling studies and its practical implementation in mass transit businesses in metropolitan areas. First, there is a short overview of past studies in the field. Subsequently, the restrictions and problems with crew scheduling and some models, which have been developed to solve the related issues with their mathematical formulation, are defined. The comments are completed by a description of the solution opportunities provided by computer-aided scheduling program systems for operational use and exposures from urban mass transit organizations. Furthermore, Bus scheduling is performed using the Hungarian technique of problem-solving tasks and mathematical modeling. Afterward, the crew scheduling problem, which consists of developing duties using predefined tasks with set start and end times and places, is resolved. Each duty has to comply with a set line of work. The objective is to minimize a mixture of fixed expenses (number of duties) and varying costs. After the optimization of cost, the outcome of the research is that the same frequency can be provided with fewer buses and less workforce.

Keywords: crew scheduling, duty, optimization of cost, urban mass transit

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Authors: Halil Ibrahim Demir, Caner Erden, Mumtaz Ipek, Ozer Uygun

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Traditionally, the three important manufacturing functions, which are process planning, scheduling and due-date assignment, are performed separately and sequentially. For couple of decades, hundreds of studies are done on integrated process planning and scheduling problems and numerous researches are performed on scheduling with due date assignment problem, but unfortunately the integration of these three important functions are not adequately addressed. Here, the integration of these three important functions is studied by using genetic, random-genetic hybrid, simulated annealing, random-simulated annealing hybrid and random search techniques. As well, the importance of the integration of these three functions and the power of meta-heuristics and of hybrid heuristics are studied.

Keywords: process planning, weighted scheduling, weighted due-date assignment, genetic search, simulated annealing, hybrid meta-heuristics

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Authors: Zaid Jamal Saeed Almahmoud

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Smart grid is emerging as the future power grid, with smart techniques to optimize power consumption and electricity generation. Minimizing peak power consumption under a fixed delay requirement is a significant problem in the smart grid.For this problem, all appliances must be scheduled within a given finite time duration. We consider the problem of minimizing the peak demand under appliances constraints by scheduling power jobs with uniform release dates and deadlines. As the problem is known to be NP-hard, we analyze the performance of a version of the natural greedy heuristic for solving this problem. Our theoretical analysis and experimental results show that the proposed heuristic outperforms existing methods by providing a better approximation to the optimal solution.

Keywords: peak demand scheduling, approximation algorithms, smart grid, heuristics

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Authors: Supattra Kanchanopast

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The purpose of this research is to develop and design a management information system for 7 eleven shop in Bangkok. The system was designed and developed to meet users’ requirements via the internet network by use of application software such as My SQL for database management, Apache HTTP Server for Web Server and PHP Hypertext Preprocessor for an interface between web server, database and users. The system was designed into two subsystems as the main system, or system for head office, and the branch system for branch shops. These consisted of three parts which are classified by user management as shop management, inventory management and Point of Sale (POS) management. The implementation of the MIS for the mini-mart shop, can lessen the amount of paperwork and reduce repeating tasks so it may decrease the capital of the business and support an extension of branches in the future as well.

Keywords: convenience store, the management information system, inventory management, 7 eleven shop

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Authors: Punya Tepsing

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This research aimed to study the beliefs in auspicious materials of entrepreneurs in Muang Hat Yai. The data were collected via documentary research and field work including interviews, observations shops in Hat Yai which used auspicious materials to bring lucks to the shops. The results were as follows. The beliefs in auspicious materials that the entrepreneurs had were of three areas: 1) The auspicious materials could correct the improperness of the shop location, for example, the shop situated opposite a branch road, a shrine, or a bank. The owner usually corrected it by putting Chinese auspicious materials in front of or in the shop, for example, a lion holding a sword in his mouth, or a mirror, etc. 2) The auspicious materials could bring in more income. The owner of the shop usually put the auspicious materials such as a cat beckoning and a bamboo fish trap believed to trap money in front of or inside the shop. 3) The auspicious materials like turtles, paired fish and a monster holding the moon in his mouth could solve life problems including health, family, and safety problems. The use of these auspicious materials showed the blending of the beliefs of the Chinese shop entrepreneurs with the Thai folk beliefs. What is interesting is that Hat Yai is located near the three southern border provinces which are the unrest area and this may cause the number of tourists to decline. This prompted them to build a mechanism in adjusting themselves both to save their lives and to increase the number of customers. Auspicious materials can make them feel more confident.

Keywords: belief, auspicious materials, shop, entrepreneur, Maung Hat Yai

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Authors: Babak H. Tabrizi, Seyed Farid Ghaderi

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Concurrent planning of project scheduling and material ordering can provide more flexibility to the project scheduling problem, as the project execution costs can be enhanced. Hence, the issue has been taken into account in this paper. To do so, a mixed-integer mathematical model is developed which considers the aforementioned flexibility, in addition to the materials quantity discount and space availability restrictions. Moreover, the activities duration has been treated as decision variables. Finally, the efficiency of the proposed model is tested by different instances. Additionally, the influence of the aforementioned parameters is investigated on the model performance.

Keywords: material ordering, project scheduling, quantity discount, space availability

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Authors: M. Moharami Gargari, S. Javdani Zamani, A. Mohammadnejad, S. Abuali

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As maritime container transport is developing fast, the need arises for efficient operations at container terminals. One of the most important determinants of container handling efficiency is the productivity of quay cranes and internal transportation vehicles, which are responsible transporting of containers for unloading and loading operations for container vessels. For this reason, this paper presents an integrated mathematical model formulation for discrete berths with quay cranes and internal transportations vehicles. The problems have received increasing attention in the literature and the present paper deals with the integration of these interrelated problems. A new mixed integer linear formulation is developed for the Berth Allocation Problem (BAP), Quay Crane Assignment and Scheduling Problem (QCASP) and Internal Transportation Scheduling (ITS), which accounts for cranes and trucks positioning conditions.

Keywords: discrete berths, container terminal, truck scheduling, dynamic vessel arrival

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Authors: Anju Bala, Inderveer Chana

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Task scheduling is the key concern for the execution of performance-driven workflow applications. As efficient scheduling can have major impact on the performance of the system, task scheduling is often chosen for assigning the request to resources in an efficient way based on cloud resource characteristics. In this paper, priority based task scheduling algorithm has been proposed that prioritizes the tasks based on the length of the instructions. The proposed scheduling approach prioritize the tasks of Cloud applications according to the limits set by six sigma control charts based on dynamic threshold values. Further, the proposed algorithm has been validated through the CloudSim toolkit. The experimental results demonstrate that the proposed algorithm is effective for handling multiple task lists from workflows and in considerably reducing Makespan and Execution time.

Keywords: cloud computing, priority based scheduling, task scheduling, VM allocation

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Authors: Irina Maria Artinescu, Costin Radu Boldea, Eduard-Ionut Matei

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The paper is a comparative study of two classical variants of parallel projection methods for solving the convex feasibility problem with their equivalents that involve variable weights in the construction of the solutions. We used a graphical representation of these methods for inpainting a convex area of an image in order to investigate their effectiveness in image reconstruction applications. We also presented a numerical analysis of the convergence of these four algorithms in terms of the average number of steps and execution time in classical CPU and, alternatively, in parallel GPU implementation.

Keywords: convex feasibility problem, convergence analysis, inpainting, parallel projection methods

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Authors: Zhangquan Zhou, Guilin Qi

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Materialization is an important reasoning service for applications built on the Web Ontology Language (OWL). To make materialization efficient in practice, current research focuses on deciding tractability of an ontology language and designing parallel reasoning algorithms. However, some well-known large-scale ontologies, such as YAGO, have been shown to have good performance for parallel reasoning, but they are expressed in ontology languages that are not parallelly tractable, i.e., the reasoning is inherently sequential in the worst case. This motivates us to study the problem of parallel tractability of ontology materialization from a theoretical perspective. That is we aim to identify the ontologies for which materialization is parallelly tractable, i.e., in the NC complexity. Since the NC complexity is defined based on Boolean circuit that is widely used to investigate parallel computing problems, we first transform the problem of materialization to evaluation of Boolean circuits, and then study the problem of parallel tractability based on circuits. In this work, we focus on datalog rewritable ontology languages. We use Boolean circuits to identify two classes of datalog rewritable ontologies (called parallelly tractable classes) such that materialization over them is parallelly tractable. We further investigate the parallel tractability of materialization of a datalog rewritable OWL fragment DHL (Description Horn Logic). Based on the above results, we analyze real-world datasets and show that many ontologies expressed in DHL belong to the parallelly tractable classes.

Keywords: ontology materialization, parallel reasoning, datalog, Boolean circuit

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Authors: Martha E. Ndeley

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Operation management is the key element within the manufacturing process. However, during this process, there are a number of unforeseen disruptions that causes the process to a standstill which are, machine breakdown, employees absenteeism, improper scheduling. When this happens, it forces the shop flow to a rescheduling process and these strategy reschedules only a limited part of the initial schedule to match up with the pre-schedule at some point with the objective to create a new schedule that is reliable which in the long run gets disrupted. In this work, we have developed feedback control system that minimizes any form of disruption before the impact becomes severe, the model was tested in a paper manufacturing industries and the results revealed that, if the disruption is minimized at the initial state, the impact becomes unnoticeable.

Keywords: disruption, machine, absenteeism, scheduling

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Authors: Wuthichai Wongthatsanekorn, Nuntana Matheekrieangkrai

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This research proposes Bee Algorithm (BA) to optimize Ready Mixed Concrete (RMC) truck scheduling problem from single batch plant to multiple construction sites. This problem is considered as an NP-hard constrained combinatorial optimization problem. This paper provides the details of the RMC dispatching process and its related constraints. BA was then developed to minimize total waiting time of RMC trucks while satisfying all constraints. The performance of BA is then evaluated on two benchmark problems (3 and 5construction sites) according to previous researchers. The simulation results of BA are compared in term of efficiency and accuracy with Genetic Algorithm (GA) and all problems show that BA approach outperforms GA in term of efficiency and accuracy to obtain optimal solution. Hence, BA approach could be practically implemented to obtain the best schedule.

Keywords: bee colony optimization, ready mixed concrete problem, ruck scheduling, multiple construction sites

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Authors: Su Xiaohan, Jin Chicheng, Liu Yijing, Burra Venkata Durga Kumar

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Energy-aware scheduling in real-time systems aims to minimize energy consumption, but issues related to resource reservation and timing constraints remain challenges. This study focuses on analyzing two scheduling algorithms, Fair-Share Scheduling (FFS) and Priority-Driven Preemptive Scheduling (PDPS), for solving these issues and energy-aware scheduling in real-time systems. Based on research on both algorithms and the processes of solving two problems, it can be found that Fair-Share Scheduling ensures fair allocation of resources but needs to improve with an imbalanced system load, and Priority-Driven Preemptive Scheduling prioritizes tasks based on criticality to meet timing constraints through preemption but relies heavily on task prioritization and may not be energy efficient. Therefore, improvements to both algorithms with energy-aware features will be proposed. Future work should focus on developing hybrid scheduling techniques that minimize energy consumption through intelligent task prioritization, resource allocation, and meeting time constraints.

Keywords: energy-aware scheduling, fair-share scheduling, priority-driven preemptive scheduling, real-time systems, optimization, resource reservation, timing constraints

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Authors: Jose Francisco Ferreira Ribeiro, Alexandre Bevilacqua Leoneti, Andre Lucirton Costa

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This paper presents a mathematical model in binary variables 0/1 to make the assignment of surgical procedures to the operating rooms in a hospital. The proposed mathematical model is based on the generalized assignment problem, which maximizes the sum of preferences for the use of the operating rooms by doctors, respecting the time available in each room. The corresponding program was written in Visual Basic of Microsoft Excel, and tested to schedule surgeries at St. Lydia Hospital in Ribeirao Preto, Brazil.

Keywords: generalized assignment problem, logistics, optimization, scheduling

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Authors: Nhat-To Huynh, Chen-Fu Chien

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Textile batch dyeing scheduling problem is complicated which includes batch formation, batch assignment on machines, batch sequencing with sequence-dependent setup time. Most manufacturers schedule their orders manually that are time consuming and inefficient. More power methods are needed to improve the solution. Motivated by the real needs, this study aims to propose approaches in which genetic algorithm is developed with multi-subpopulation and hybridised with estimation of distribution algorithm to solve the constructed problem for minimising the makespan. A heuristic algorithm is designed and embedded into the proposed algorithms to improve the ability to get out of the local optima. In addition, an empirical study is conducted in a textile company in Taiwan to validate the proposed approaches. The results have showed that proposed approaches are more efficient than simulated annealing algorithm.

Keywords: estimation of distribution algorithm, genetic algorithm, multi-subpopulation, scheduling, textile dyeing

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Authors: Wen-Tsung Ho, Ku-Kuang Chang, Hsin-Yuan Chang

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In this study, we consider an economic lot-size batch-shipment scheduling problem (ELBSP) with extended basic period (EBP) and power-of-two (PoT) policies. In this problem, the supplier using a single facility to manufacture multiple products and equally sized batches are then delivered by the supplier to buyers over an infinite planning horizon. Further, the extended basic period (EBP) and power-of-two (PoT) policy are utilized. Relaxing the production schedule converts the ELBSP to an economic lot-size batch-shipment problem (ELBP) with EBP and PoT policies, and a nonlinear integer programming model of the ELBP is constructed. Using the replenishment cycle division and recursive tightening methods, optimal solutions are then solved separately for each product. The sum of these optimal solutions is the lower bound of the ELBSP. A proposed heuristic method with polynomial complexity is then applied to figure out the near-optimal solutions of the ELBSP. Numerical example is presented to confirm the efficacy of the proposed method.

Keywords: economic lot-size scheduling problem, extended basic period, replenishment cycle division, recursive tightening, power-of-two

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Authors: H. M. Soroush

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The problem of scheduling products and services for on-time deliveries is of paramount importance in today’s competitive environments. It arises in many manufacturing and service organizations where it is desirable to complete jobs (products or services) with different weights (penalties) on or before their due dates. In such environments, schedules should frequently decide whether to schedule a job based on its processing time, due-date, and the penalty for tardy delivery to improve the system performance. For example, it is common to measure the weighted number of late jobs or the percentage of on-time shipments to evaluate the performance of a semiconductor production facility or an automobile assembly line. In this paper, we address the problem of scheduling a set of jobs on a server where processing times or due-dates of jobs are random variables and fixed weights (penalties) are imposed on the jobs’ late deliveries. The goal is to find the schedule that minimizes the expected weighted number of tardy jobs. The problem is NP-hard to solve; however, we explore three scenarios of the problem wherein: (i) both processing times and due-dates are stochastic; (ii) processing times are stochastic and due-dates are deterministic; and (iii) processing times are deterministic and due-dates are stochastic. We prove that special cases of these scenarios are solvable optimally in polynomial time, and introduce efficient heuristic methods for the general cases. Our computational results show that the heuristics perform well in yielding either optimal or near optimal sequences. The results also demonstrate that the stochasticity of processing times or due-dates can affect scheduling decisions. Moreover, the proposed problem is general in the sense that its special cases reduce to some new and some classical stochastic single machine models.

Keywords: number of late jobs, scheduling, single server, stochastic

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Authors: Salam Saudagar, Ankit Kamboj, Niraj Mohan, Satgounda Patil, Nilesh Powar

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Task Assignment and Scheduling is a challenging Operations Research problem when there is a limited number of resources and comparatively higher number of tasks. The Cost Management team at Cummins needs to assign tasks based on a deadline and must prioritize some of the tasks as per business requirements. Moreover, there is a constraint on the resources that assignment of tasks should be done based on an individual skill level, that may vary for different tasks. Another constraint is for scheduling the tasks that should be evenly distributed in terms of number of working hours, which adds further complexity to this problem. The proposed greedy approach to solve assignment and scheduling problem first assigns the task based on management priority and then by the closest deadline. This is followed by an iterative selection of an available resource with the least allocated total working hours for a task, i.e. finding the local optimal choice for each task with the goal of determining the global optimum. The greedy approach task allocation is compared with a variant of Hungarian Algorithm, and it is observed that the proposed approach gives an equal allocation of working hours among the resources. The comparative study of the proposed approach is also done with manual task allocation and it is noted that the visibility of the task timeline has increased from 2 months to 6 months. An interactive dashboard app is created for the greedy assignment and scheduling approach and the tasks with more than 2 months horizon that were waiting in a queue without a delivery date initially are now analyzed effectively by the business with expected timelines for completion.

Keywords: assignment, deadline, greedy approach, Hungarian algorithm, operations research, scheduling

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