Multi-objective assembly job shop scheduling using genetic algorithm and tabu search

Assembly job shop scheduling problem (AJSP) is one of the most complicated combinatorial optimization problem that involves simultaneously scheduling the processing and assembly operations of complex structured products. The problem becomes even more complicated if a combination of two or more optimization criteria is considered. This thesis addresses an assembly job shop scheduling problem with multiple objectives. The objectives considered are to simultaneously minimizing makespan and total tardiness. In this thesis, two approaches viz., weighted approach and Pareto approach are used for solving the problem. However, it is quite difficult to achieve an optimal solution to this problem with traditional optimization approaches owing to the high computational complexity. Two metaheuristic techniques namely, genetic algorithm and tabu search are investigated in this thesis for solving the multiobjective assembly job shop scheduling problems. Three algorithms based on the two metaheuristic techniques for weighted approach and Pareto approach are proposed for the multi-objective assembly job shop scheduling problem (MOAJSP). A new pairing mechanism is developed for crossover operation in genetic algorithm which leads to improved solutions and faster convergence. The performances of the proposed algorithms are evaluated through a set of test problems and the results are reported. The results reveal that the proposed algorithms based on weighted approach are feasible and effective for solving MOAJSP instances according to the weight assigned to each objective criterion and the proposed algorithms based on Pareto approach are capable of producing a number of good Pareto optimal scheduling plans for MOAJSP instances.

Solving a multiobjective job shop scheduling problem using Pareto Archived Cuckoo Search

This paper investigates a new approach for solving the multiobjective job shop scheduling problem, namely the Cuckoo Search ( CS) approach. The requirement is to schedule jobs on a single machine so that the total material waste is minimised as well as the total tardiness time. The material waste is quantified in terms of saving factors to show the reduction in material that can be achieved when producing two jobs with the same materials in sequence. The estimated saving factor is used to calculate a cost savings for each job based on its material type. A formulation of multiobjective optimisation problems is adopted to generate the set of schedules that maximise the overall cost savings and minimise the total tardiness time. where all trade-offs are considered for the two conflicting objectives. A Pareto Archived Multiobjective Cuckoo Search (PAMOCS) is developed to find the set ofnondominated Pareto optimal solutions. The solution accuracy of PAMOCS is shown by comparing the closeness of the obtained solutions to the true Pareto front generated by the complete enumeration methad. Results shaw that CS is a very effective and promising technique to solve job shop scheduling problems.

Job-shadowing: Swiss health librarians observing experienced search specialists and information skills trainers in London

Abstract As librarians of the Social & Preventive Medicine Library in Bern, we help researchers perform systematic literature searches and teach students to use medical databases. We developed our skills mainly “on the job”, and we wondered how other health librarians in Europe were trained to become experts in searching. We had a great opportunity to “job shadow” specialists in this area of library service during a 5-day-internship at the Royal Free Hospital Medical Library in London, Great Britain.

Factors contributing to nurse job satisfaction in the acute hospital setting : a review of recent literature

Aim  To explore and discuss from recent literature the common factors contributing to nurse job satisfaction in the acute hospital setting. Background  Nursing dissatisfaction is linked to high rates of nurses leaving the profession, poor morale, poor patient outcomes and increased financial expenditure. Understanding factors that contribute to job satisfaction could increase nurse retention. Evaluation  A literature search from January 2004 to March 2009 was conducted using the keywords nursing, (dis)satisfaction, job (dis)satisfaction to identify factors contributing to satisfaction for nurses working in acute hospital settings. Key issues  This review identified 44 factors in three clusters (intra-, inter- and extra-personal). Job satisfaction for nurses in acute hospitals can be influenced by a combination of any or all of these factors. Important factors included coping strategies, autonomy, co-worker interaction, direct patient care, organizational policies, resource adequacy and educational opportunities. Conclusions  Research suggests that job satisfaction is a complex and multifactorial phenomenon. Collaboration between individual nurses, their managers and others is crucial to increase nursing satisfaction with their job. Implications for nursing management  Recognition and regular reviewing by nurse managers of factors that contribute to job satisfaction for nurses working in acute care areas is pivotal to the retention of valued staff.

A hybrid shifting bottleneck procedure algorithm for the parallel-machine job-shop scheduling problem

In practice, parallel-machine job-shop scheduling (PMJSS) is very useful in the development of standard modelling approaches and generic solution techniques for many real-world scheduling problems. In this paper, based on the analysis of structural properties in an extended disjunctive graph model, a hybrid shifting bottleneck procedure (HSBP) algorithm combined with Tabu Search metaheuristic algorithm is developed to deal with the PMJSS problem. The original-version SBP algorithm for the job-shop scheduling (JSS) has been significantly improved to solve the PMJSS problem with four novelties: i) a topological-sequence algorithm is proposed to decompose the PMJSS problem into a set of single-machine scheduling (SMS) and/or parallel-machine scheduling (PMS) subproblems; ii) a modified Carlier algorithm based on the proposed lemmas and the proofs is developed to solve the SMS subproblem; iii) the Jackson rule is extended to solve the PMS subproblem; iv) a Tabu Search metaheuristic algorithm is embedded under the framework of SBP to optimise the JSS and PMJSS cases. The computational experiments show that the proposed HSBP is very efficient in solving the JSS and PMJSS problems.

A fast tabu search algorithm for the group shop scheduling problem

Three types of shop scheduling problems, the flow shop, the job shop and the open shop scheduling problems, have been widely studied in the literature. However, very few articles address the group shop scheduling problem introduced in 1997, which is a general formulation that covers the three above mentioned shop scheduling problems and the mixed shop scheduling problem. In this paper, we apply tabu search to the group shop scheduling problem and evaluate the performance of the algorithm on a set of benchmark problems. The computational results show that our tabu search algorithm is typically more efficient and faster than the other methods proposed in the literature. Furthermore, the proposed tabu search method has found some new best solutions of the benchmark instances.

Heuristics for Job-Shop Scheduling

Two methods of obtaining approximate solutions to the classic General Job-shop Scheduling Program are investigated. The first method is iterative. A sampling of the solution space is used to decide which of a collection of space pruning constraints are consistent with "good" schedules. The selected space pruning constraints are then used to reduce the search space and the sampling is repeated. This approach can be used either to verify whether some set of space pruning constraints can prune with discrimination or to generate solutions directly. Schedules can be represented as trajectories through a Cartesian space. Under the objective criteria of Minimum maximum Lateness family of "good" schedules (trajectories) are geometric neighbors (reside with some "tube") in this space. This second method of generating solutions takes advantage of this adjacency by pruning the space from the outside in thus converging gradually upon this "tube." One the average this methods significantly outperforms an array of the Priority Dispatch rules when the object criteria is that of Minimum Maximum Lateness. It also compares favorably with a recent relaxation procedure.

Optimised search heuristics: combining metaheuristics and exact methods to solve scheduling problems

Tese dout., Matemática, Investigação Operacional, Universidade do Algarve, 2009

The impact of job insecurity on adaptive performance via burnout

Difficult and unpredictable times, due to economic instability, lead employees to feel high job insecurity. Organizations’ only way to subsistence is to search innovative ways of solving problems and find creative solutions. This study focuses on the impact that job insecurity has on adaptive performance, a recent measure integrating the response of creativity, reactivity in the face of emergencies, interpersonal adaptability, training effort, and handling work stress, and, mediated by burnout. From the responses of two questionnaires (????????1=252; ????????2=145), we conclude that job insecurity leads to exhaustion, but not to disengagement. In turn, it is the latter that demonstrates to have negative relations with some measures of adaptive performance. Thus, it is crucial to understand how organizations can minimize the inherent process.

Identifying job skills in commercial advisors in a health insurance company

The aim of this research was to identify the criticalcompetence of success of the commercial adviserin a company providing insurance and health services.For this research a sample of 34 commercialadvisers. The sample was divided into four groups(two per product and two per criterion of success).Systematic fi eld observations, interviews of criticalincidents, application of response tests and salesworkshops were used to evaluate the differentialcompetences that the successful advisers wereshowing in relation to the advisers de fi ned as average.The success criteria were based on the generatedcommission performance over the 10 months. Allin all, signi fi cant differences were found betweenthe “successful” and “average” groups. Furthermore,competences that correlate positively with atop sales performance were observed and competencesthat have major level of discrimination betweenthe “successful” and “average” groups wereestablished. Orientation to achievement, planningand management, information search, commercialaggressiveness and strategic vision are the competencesthat were considered to be key in the topperformance of a sales agent or commercial adviser.Additionally, the results in the response testswere analyzed in the four study groups, withoutobserving signi fi cant differences between them,which supports the theoretical framework of thepresent study.

Decentralized load balancing for highly irregular search problems

In this paper, we present a distributed computing framework for problems characterized by a highly irregular search tree, whereby no reliable workload prediction is available. The framework is based on a peer-to-peer computing environment and dynamic load balancing. The system allows for dynamic resource aggregation, does not depend on any specific meta-computing middleware and is suitable for large-scale, multi-domain, heterogeneous environments, such as computational Grids. Dynamic load balancing policies based on global statistics are known to provide optimal load balancing performance, while randomized techniques provide high scalability. The proposed method combines both advantages and adopts distributed job-pools and a randomized polling technique. The framework has been successfully adopted in a parallel search algorithm for subgraph mining and evaluated on a molecular compounds dataset. The parallel application has shown good calability and close-to linear speedup in a distributed network of workstations.

Employer satisfaction, job-match and future hiring intentions for employees with a disability

This paper is based on survey responses from 656 employers who used disability employment services to employ someone with a disability. Relationships between employer satisfaction and employer perceptions of job-match and future hiring intentions toward people who have a disability are outlined and discussed. Employers' perceptions of the job-match process were found to be an important determinant of their perceptions of work performance and employer satisfaction. Comparative ratings on employer satisfaction for employees with and without a disability were seen as an important indicator of future hiring intentions toward people with a disability. Findings reported in this paper provide important information on which to base strategies for improving future employment outcomes for people who have a disability.

`Just give me someone who can hit the ground running`: an investigation into the job-ready public relations graduate

Public relations educators perform an academic and vocational balancing act. Employers demand graduates with developed vocational skills. In the meantime, academics strive to provide students with work skills as well as solid theoretical base, and to also address emerging issues. This paper uses a case study in Geelong, Victoria to examine what Australian regional employers see as desirable attributes in public relations graduates. It then explores how educators address the needs of the employers as well as the needs of the public relations profession.

The right tool for the job? Use of the multiple intelligences and Bloom's taxonomy grid

This article explores the tacit understanding of teachers in the field of gifted educational practices after their participation in gifted education professional development. The data for this article are drawn from a single-case qualitative study where semi-structured interviews were held with teachers, administrators and support staff in a metropolitan Victorian primary school. The findings lead to two main arguments: first, that some teachers preserved their deeply entrenched beliefs and assumptions about the gifted, the talented and intelligence[s]; and second, that teachers, without critical examination, eagerly adopted and adapted Gardner's Multiple Intelligences theory, overlaid with Bloom's Revised Taxonomy of Thinking as a means for addressing individual differences in the classroom. The article argues that teachers welcomed the Gardner/Bloom matrix for its 'tick-the-box' simplicity, with little insight into the theoretical models. Whilst the matrix had an immediate value in the mixed ability classrooms, in the long term it did not support the learning needs of gifted students. [Author abstract]

Pareto archived simulated annealing for single machine job shop scheduling with multiple objectives

In this paper, the single machine job shop scheduling problem is studied with the objectives of minimizing the tardiness and the material cost of jobs. The simultaneous consideration of these objectives is the multi-criteria optimization problem under study. A metaheuristic procedure based on simulated annealing is proposed to find the approximate Pareto optimal (non-dominated) solutions. The two objectives are combined in one composite utility function based on the decision maker’s interest in having a schedule with weighted combination. In view of the unknown nature of the weights for the defined objectives, a priori approach is applied to search for the non-dominated set of solutions based on the Pareto dominance. The obtained solutions set is presented to the decision maker to choose the best solution according to his preferences. The performance of the algorithm is evaluated in terms of the number of non-dominated schedules generated and the proximity of the obtained non-dominated front to the true Pareto front. Results show that the produced solutions do not differ significantly from the optimal solutions.