Job Delivery Research Articles

Office information technologies and performance of Tertiary institutions in Southeast Nigeria

The study examined office information technologies and performance of Tertiary institutions in Southeast Nigeria. Specifically, the study sought to: investigate the influence of printer on employee job performance of tertiary institutions and ascertain the influence of photocopy machine on quality job delivery of tertiary institutions. Research design was descriptive survey research. Sample size of 378 respondents were drawn from 5,503 academic staff of three selected tertiary institutions in Southeast Nigeria namely University of Nigeria Nsukka, Nnamdi Azikiwe University Awka, Michael Okpara University of Agriculture Umudike and Ebonyi State University Abakiliki. The hypotheses were tested with regression analysis comprising student-t statistics. The empirical results show printer has significant influence on employee job performance of tertiary institutions in Southeast in Nigeria (t-statistics (9.292) > P-value (0.000) and photocopy machine has significant influence on quality job delivery of tertiary institutions in Southeast in Nigeria (t-statistics (6.312) > P-value (0.000). The study recommended that management of tertiary institutions in Nigeria should adopt the idea of using up-to-date information technology devices/tools so as avoid obsolescence so as to improve the service delivery.

Enabling CMS Experiment to the utilization of multiple hardware architectures: a Power9 Testbed at CINECA

The CMS software stack (CMSSW) is built on a nightly basis for multiple hardware architectures and compilers, in order to benefit from the diverse platforms. In practice, still, only x86_64 binaries are used in production, and are supported by the workload management tools in charge of production and analysis job delivery to the distributed computing infrastructure. Profiting from an INFN grant at CINECA, a PRACE Tier-0 Center, tests have been carried on using IBM Power9 nodes from the Marconi100 HPC system. A first study on the modifications needed to the standard CMS WMS systems is shown, and very positive proof-of-concept tests have been conducted up to thousands of computing cores, also including an initial utilization of the GPUs which the nodes host. The current status of the tests, including plans to support multi-architecture workflows, are shown and discussed.

Online scheduling on parallel-batch machines with periodic availability constraints and job delivery

We address an online scheduling problem on identical parallel-batch machines with periodic availability constraints and job delivery. A parallel-batch machine can process several jobs simultaneously in a batch without any preemption. The processing time of a batch is equal to the maximum processing time of the jobs in this batch, and the job processing times we consider are identical on all machines. Available and unavailable time intervals occur alternately on machines. The unavailable time intervals have the same start and end time on different machines. Jobs are released over time, which means that no information of the job is known in advance before its release date. After completion, job is delivered to customer. Three objective functions, namely, maximum flow time, maximum delivery time and total flow time are considered separately. For these objectives, we derive lower bounds on competitive ratios, provide online algorithms and analyze their competitive ratios.

Solving a stochastic hierarchical scheduling problem by VNS-based metaheuristic with locally assisted algorithms

High-end equipment manufacture has features of intensive technology, uncertain process, and large scale. Hence, the scheduling of the High-end equipment manufacture is challenging. Large ships are a type of High-end equipment that is tied to national maritime security. In this paper, we study a stochastic hierarchical scheduling problem with serial-batch processing machines and the deterioration effect in ship manufacture. In the studied problem, the job processing time is uncertain and follows a normal probability distribution. Under the deterioration effect, the actual processing time of jobs is formulated as a function of the start time. The first objective is to maximize the robustness of the manufacturing system. The second objective is to minimize the total inventory cost subjected to the optimization of the first objective. The robustness of the manufacturing system is measured by the worst level of completion probability. The total inventory cost is measured by the difference between the job delivery time and the job completion time. The mathematical model for the studied problem is formulated. Some structural properties are derived to solve the problem. Based on the properties, the optimal sequence for the first objective can be obtained and a heuristic algorithm is designed to optimize the second objective. The considered problem is NP-hard involving several non-linearities. Hence, a variable neighborhood search (VNS) algorithm is developed to solve the problem in a reasonable time, which is integrated with three local search strategies and a heuristic algorithm. Various problem instances are generated and extensive computational experiments verify that the proposed VNS algorithm outperforms other compared algorithms and has strong robustness.

A Review of Workplace Conflicts and Employee Performance in Tamale Metropolitan Assembly of Northern Region, Ghana

The study investigated the effects of workplace conflict on employee performance at the Tamale Metropolitan Assembly from where a sample of 194 was drawn. The study adopted descriptive research design. Data was collected with questionnaires, analyzed with SPSS version 26 and the results presented in tables, interpreted and discussed. Results showed that workplace conflicts in TMA were largely interpersonal. Poor communication was rated the highest cause of the conflicts. Negative effects of the conflicts include: reduction of morale of workers, creation of tension and anxiety that weakens abilities of employees to work well, lack of essential information needed for effective job delivery, delayed delivery of assignments and project failures. Positive outcomes of the conflicts are that: they increase employees’ creativity and innovation towards doing things, strengthen bonds and improve relationships when well-managed, they bring on board effective and efficient utilization of scarce resources in the Assembly emanating from best decisions. The study concluded that the overall effect of conflicts in TMA on employees’ performance is negative; resulting in non-optimization of employees’ output. The study recommended that the Assembly should allow free flow of information by improving communication to establish problems facing employees and to promptly address them. Keywords: Organization, Workplace, Conflicts, Performance, Outcomes DOI: 10.7176/EJBM/14-16-01 Publication date: August 31 st 2022

Exact and matheuristic methods for the parallel machine scheduling and location problem with delivery time and due date

The scheduling and location (ScheLoc) problem is a new and important research topic with a wide range of practical applications. It jointly optimizes machine locations, job assignments, and sequence decisions to yield a globally optimal solution. Current studies on the ScheLoc problem are limited, and most have focused on makespan minimization. This paper investigates a new variant of the parallel-machine ScheLoc problem with job delivery time and due date considerations. This is motivated by practical situations where jobs must be transported back to their original locations upon completion of processing, and a specific due date is associated with each job. The objective is to minimize the total weighted sum of location, transportation, and tardiness penalty costs incurred if a job is delivered after its due date. We propose three models adapted from classic ones for scheduling problems. We then develop an exact logic-based Benders decomposition method, which decomposes the problem into a master problem (MP) for determining machine locations and job assignments, and a subproblem (SP) for determining job sequences on each machine. The MP is augmented by dynamically adding optimality cuts generated by solving the SP. We also develop a matheuristic (MH) and its variant to achieve near-optimal solutions. An approximate model with predetermined job processing sequences on each machine is formulated and solved to determine the machine locations and job assignments. The obtained solutions are further improved by solving a series of single-machine scheduling problems. The variant combines a kernel search framework to make MH more efficient. Computational experiments on 720 randomly generated instances show the effectiveness and efficiency of both the exact and matheuristic methods.

The Obstacles to Using Performance Appraisal and Reward Systems as Tools for Improving Employee Performance

Performance appraisal and incentive systems are one of the fundamental tools utilised by succeeding businesses, both public and private, in increasing employee performance, as they serve to keep employees on their toes and motivated to work for the organization's betterment. Personal bias, recent effects, spillover, and a lack of clarity in the job description are some of the characteristics that militate against using performance appraisal as a strategy for improving employee performance, according to the findings. The study suggested, among other things, the creation of a clearly defined benchmark for rewarding employees who perform exceptionally well in their job delivery. This is to ensure transparency in the process of rewarding employees for a job well done, as this will encourage others to perform better. Finally, a performance appraisal should not only be based on an employee's recent performance or spill-over, personal bias but the employee's overall performance over the period under review.

Effect of internet banking on the performance of small-medium enterprises in Enugu metropolis

The study examined the effect of internet banking on small and medium enterprises performance in Enugu Metropolis. Specifically this study aims to determine the (i) the effect of internet effectiveness on small and medium enterprises business expansion in Enugu Metropolis, and (ii) the effect of internet convenience on small and medium enterprise quality of job delivery in Enugu Metropolis. The study made use of descriptive survey design. The study used structured questionnaire to obtain data. The population of the study is 650 with sample size of 264. Summary of the study includes: the findings of the study revealed that internet effectiveness has significant effect on small and medium enterprises business expansion in Enugu metropolis (t – statistics (38.887) > P – value (0.000), the findings of the study also revealed that internet convenience has significant effect on small and medium enterprise quality of job delivery in Enugu metropolis (t – statistics (33.446) > P – value (0.000), and the findings of the study revealed that internet accessibility has significant effect on small and medium enterprise expansion of income base in Enugu metropolis, because internet accessibility enables to conduct banking business over the internet where costs are minimal, since (t – statistics (51.826) > P – value (0.000). The study recommends that small and medium enterprises should organize training on internet banking from time to time for the benefit of its customers; this will go a long way to enhance the benefits derived by the bank from internet banking.

A Non-Dominated Genetic Algorithm Based on Decoding Rule of Heat Treatment Equipment Volume and Job Delivery Date

This paper investigated the flexible job-shop scheduling problem with the heat treatment process. To solve this problem, we built an unified mathematical model of the heat treatment process and machining process. Up to now, this problem has not been investigated much. Based on the features of this problem, we are intended to minimize Cmax, maximize the space utilization rate of heat treatment equipment, and minimize the total delay penalty to optimize the scheduling. By taking the dynamic process arrival under consideration, this paper proposed a set of decoding rules based on the heat treatment equipment volume and job delivery date to achieve a hybrid dynamic scheduling solution during one scheduling procedure. When the utilization rate of heat treatment equipment volume is maximized, and the job delivery date is taken under consideration, it is preferred to minimize the number of workpiece batches in the same job, and reduce the waiting time of the pending job. In combination with the improved adaptive non-dominated genetic algorithm, we worked out the solution. Furthermore, we verified the effectiveness of the proposed decoding rules and improved algorithm through algorithm comparison and calculation results. Finally, a software system for algorithm verification and algorithm comparison was developed to verify the validity of our proposed algorithm.

Theoretical and practical issues in single-machine scheduling with two job release and delivery times

Theoretical and practical issues in single-machine scheduling with two job release and delivery times

Branch Less, Cut More and Schedule Jobs with Release and Delivery Times on Uniform Machines

We consider the problem of scheduling n jobs with identical processing times and given release as well as delivery times on m uniform machines. The goal is to minimize the makespan, i.e., the maximum full completion time of any job. This problem is well-known to have an open complexity status even if the number of jobs is fixed. We present a polynomial-time algorithm for the problem which is based on the earlier introduced algorithmic framework blesscmore (“branch less and cut more”). We extend the analysis of the so-called behavior alternatives developed earlier for the version of the problem with identical parallel machines and show how the earlier used technique for identical machines can be extended to the uniform machine environment if a special condition on the job parameters is imposed. The time complexity of the proposed algorithm is O(γm2nlogn), where γ can be either n or the maximum job delivery time qmax. This complexity can even be reduced further by using a smaller number κ<n in the estimation describing the number of jobs of particular types. However, this number κ becomes only known when the algorithm has terminated.

Towards a framework of automated resource model for post contract cost control of construction projects

Real-time control of on-site construction cost has been a major concern as every client demand value for the money invested in procuring a construction project. The design team and other stakeholders in the construction industry face the challenges posed by the ever-increasing complexity of construction facilities, and the demands of clients to meet their needs within a given budget. In addition, the trend of information technology in construction demands that all activities including cost optimization be automated and digitalized for better proficiency of the construction professionals and effectiveness of job delivery. This article presents a conceptual framework for the automated resource model (ARM) for on-site construction cost control. The concept of ARM is based on the use of mobile technology, integrating it with a back-office central system for real-time data capturing, monitoring, and control to keep expenditure within a predetermined budget. The scope covered includes Automated Real-Time Data (ARTiD) collection, Construction Progress Monitoring and Evaluation, and Construction Activity Monitoring. The ARM concept can enable the construction stakeholders to obtain information on cost implications of all activities simultaneously. It can also enable quick detection of any source of cost and time overrun and propose quick remedial action.

LBA70_PR The impact of COVID-19 on oncology professionals: Initial results of the ESMO resilience task force survey collaboration

The impact of the COVID-19 (CV-19) pandemic on wellbeing has the potential for serious negative consequences on work, home life and patient care. The ESMO Resilience Task Force collaboration set out to investigate wellbeing in oncology over time since CV-19. 2 online surveys were conducted (survey I April/May; survey II July/August 2020). Statistical analyses were used to examine group differences, associations and to explore predictors of key outcomes: 1) wellbeing/distress (Wellbeing Index (WBI-9)), 2) burnout (1 item); and 3) CV-19 job performance (2 item CJP; standard of care and job delivery compared to pre-CV 19). Survey I had 1520 participants from 101 countries. Responses indicate that CV-19 is impacting the oncology workforce resulting in a number of changes to work and personal lives. 25% were at risk of distress (poor wellbeing, WBI ≥4); 38% reported feeling burnout and 66% were not able to perform their job compared to pre-CV-19. Higher CJP was significantly associated with better wellbeing and not feeling burnout (p<0.01). Differences were seen in wellbeing and CJP between countries (p<0.001) and related to CV-19 country mortality rate (p<0.05). The main predictors of wellbeing, burnout and CJP were resilience and changes to work hours. Others frequently identified were coping strategies, ethnicity, concern about training/career, worried about current wellbeing, and working conditions. In Survey II, results from 942 participants are undergoing analysis. Overall, comparisons between surveys show overall wellbeing and burnout rates have worsened overtime but CJP has improved. Among 272 participants who completed both surveys, WBI scores ≥4 (indicating higher risk of distress) and burnout rates were higher in survey II compared to survey I (22% vs 31% p=0.01; 35% vs 49% p=0.001 respectively) suggesting wellbeing and burnout may be worsening overtime. CJP improved (38% vs 54% p<0.001). In the largest global survey series, COVID-19 is impacting on the wellbeing and job performance of oncology professionals. Risk of distress and burnout has increased over time. Urgent measures to address wellbeing and improve resilience are essential.

Two Parallel Machines Scheduling with Two-Vehicle Job Delivery to Minimize Makespan

A problem of parallel machine scheduling with coordinated job deliveries is handled to minimize the makespan. Different jobs call for dissimilar sizes of storing space in the process of transportation. A range of jobs of one customer in the problem have priority to be processed on two identical parallel machines without preemption and then delivered to the customer by two vehicles in batches. For this NP-hard problem, we first prove that it is impossible to have a polynomial heuristic with a worst-case performance ratio bound less than 2 unless P = NP. Thereafter, we develop a polynomial heuristic for this problem, the worst-case ratio of which is bounded by 2.

Extending the POLCA production control system with centralized job release

Abstract Paper aims POLCA is a production control system that forwards to gateway manufacturing cells jobs that arrive to a manufacturing system. However, Workload Control literature shows benefits from using a centralized release pre-shop pool. Thus, the paper aims at investigating the performance impact of incorporating centralized job release into POLCA, in high-variety make-to-order production. Originality This has not been investigated before. Research method Simulation was used for experimentation. Main findings In the case of the general flow shop, a manufacturing system configuration aligned with many real-world production systems, the investigation shows that adding centralized job release to the POLCA system, together with job release based on job workload, leads to a markedly improvement of job delivery performance. Implications for theory and practice The results show theoretical and practical relevance of applying central job release to POLCA system, in high-variety production, due to its markedly positive impact on delivery performance.

A -approximation algorithm for scheduling on two parallel machines with job delivery coordination

Integration of production and distribution operations at the scheduling level is one of the most important issues concerned in recent years in supply chain management. We investigate the scheduling problem with job delivery coordination. Concretely, we are given a set of jobs with non-identical processing times and non-identical sizes to be first processed by two parallel-identical machines and then delivered to a common customer by a single vehicle, which has a limited capacity that can carry up to a fixed total size of jobs in one batch. The objective is to minimize the makespan, ie, the time when all the jobs have reached the customer and the delivery vehicle has returned to the machine. The problem does not admit a polynomial time approximation algorithm with worst-case ratio smaller than unless P = NP. By introducing some novel ideas and new methods, including algorithms solving multiple knapsack problem as subprocedures and the rediscovery of the profound nature of the bin-packing algorithm, we propose a polynomial time approximation algorithm with worst-case ratio arbitrary close to . The algorithm, acquired after long-term research containing many earlier related works, is the first algorithm for this kind of problems and its theoretical performance is nearly best.

A PTAS for single-machine scheduling with release dates and job delivery to minimize makespan

We consider the single-machine scheduling problem with release dates and job delivery to minimize makespan. Preemption is not allowed in the processing of the jobs. All jobs are first processed on a single machine and then delivered by a capacitated vehicle to a single customer. The vehicle can deliver at most c ≥ 1 jobs in each shipment. The round-trip transportation time between the machine and customer is a constant T &gt; 0. The problem was proved to be strongly NP-hard and a 3/2-approximation algorithm was presented in the literature. In this paper we provide a polynomial-time approximation scheme (PTAS) for the problem.

Online Scheduling of Incompatible Family Jobs with Equal Length on an Unbounded Parallel-Batch Machine with Job Delivery

In this paper, we consider the online scheduling of incompatible family jobs with equal length on an unbounded parallel-batch machine with job delivery. The jobs arrive online over time and belong to [Formula: see text] incompatible job families, where [Formula: see text] is known in advance. The jobs are first processed in batches on an unbounded parallel-batch machine and then the completed jobs are delivered in batches by a vehicle with infinite capacity to their customers. The jobs from distinct families cannot be processed and delivered in the same batch. The objective is to minimize the maximum delivery completion time of the jobs. For this problem, we present an online algorithm with the best competitive ratio of [Formula: see text].

Parallel machine scheduling with job delivery coordination

We analyse a parallel (identical) machine scheduling problem with job delivery to a single customer. For this problem, each job needs to be processed on \(m\) parallel machines non-pre-emptively and then transported to a customer by one vehicle with a limited physical capacity. The optimization goal is to minimize the makespan, the time at which all the jobs are processed and delivered and the vehicle returns to the machine. We present an approximation algorithm with a tight worst-case performance ratio of \(7/3-1/m\) for the general case, \(m\ge 3\). doi:10.1017/S1446181117000190

Scheduling with job delivery coordination on single machine

This paper investigates a single machine scheduling problem with job delivery coordination, in which each job demands different amount of storage space during transportation. In this problem, a set of independent jobs from a customer must first be processed on a machine without preemption and then delivered by two homogeneous vehicles to the customer in batches. To minimize the makespan, we develop a best possible polynomial-time heuristic with a worst-case ratio of 2.