Search results

1 – 10 of over 82000
To view the access options for this content please click here
Article
Publication date: 25 July 2019

Yifei Ren and Zhiqiang Lu

In response to the station design and flexible resources allocation of the aircraft moving assembly line, a new problem named flexible resource investment problem based on…

Abstract

Purpose

In response to the station design and flexible resources allocation of the aircraft moving assembly line, a new problem named flexible resource investment problem based on project splitting (FRIP_PS), which minimizes total cost of resources with a given deadline are proposed in this paper.

Design/methodology/approach

First, a corresponding mathematical model considering project splitting is constructed, which needs to be simultaneously determined together with job scheduling to acquire the optimized project scheduling scheme and resource configurations. Then, an integrated nested optimization algorithm including project splitting policy and job scheduling policy is designed in this paper. In the first stage of the algorithm, a heuristic algorithm designed to get the project splitting scheme and then in the second stage a genetic algorithm with local prospective scheduling strategy is adopted to solve the flexible resource investment problem.

Findings

The heuristic algorithm of project splitting gets better project splitting results through the job shift selection strategy and meanwhile guides the algorithm of the second stage. Furthermore, the genetic algorithm solves resources allocation and job schedule through evaluation rules which can effectively solve the delayed execution of jobs because of improper allocation of flexible resources.

Originality/value

This paper represents a new extension of the resource investment problem based on aircraft moving assembly line. An effective integrated nested optimization algorithm is proposed to specify station splitting scheme, job scheduling scheme and resources allocation in the assembly lines, which is significant for practical engineering applications.

Details

Assembly Automation, vol. 39 no. 4
Type: Research Article
ISSN: 0144-5154

Keywords

To view the access options for this content please click here
Article
Publication date: 9 January 2019

Amir Hossein Hosseinian, Vahid Baradaran and Mahdi Bashiri

The purpose of this paper is to propose a new mixed-integer formulation for the time-dependent multi-skilled resource-constrained project scheduling problem (MSRCPSP/t…

Abstract

Purpose

The purpose of this paper is to propose a new mixed-integer formulation for the time-dependent multi-skilled resource-constrained project scheduling problem (MSRCPSP/t) considering learning effect. The proposed model extends the basic form of the MSRCPSP by three concepts: workforces have different efficiencies, it is possible for workforces to improve their efficiencies by learning from more efficient workers and the availability of workforces and resource requests of activities are time-dependent. To spread dexterity from more efficient workforces to others, this study has integrated the concept of diffusion maximization in social networks into the proposed model. In this respect, the diffusion of dexterity is formulated based on the linear threshold model for a network of workforces who share common skills. The proposed model is bi-objective, aiming to minimize make-span and total costs of project, simultaneously.

Design/methodology/approach

The MSRCPSP is an non-deterministic polynomial-time hard (NP-hard) problem in the strong sense. Therefore, an improved version of the non-dominated sorting genetic algorithm II (IM-NSGA-II) is developed to optimize the make-span and total costs of project, concurrently. For the proposed algorithm, this paper has designed new genetic operators that help to spread dexterity among workforces. To validate the solutions obtained by the IM-NSGA-II, four other evolutionary algorithms – the classical NSGA-II, non-dominated ranked genetic algorithm, Pareto envelope-based selection algorithm II and strength Pareto evolutionary algorithm II – are used. All algorithms are calibrated via the Taguchi method.

Findings

Comprehensive numerical tests are conducted to evaluate the performance of the IM-NSGA-II in comparison with the other four methods in terms of convergence, diversity and computational time. The computational results reveal that the IM-NSGA-II outperforms the other methods in terms of most of the metrics. Besides, a sensitivity analysis is implemented to investigate the impact of learning on objective function values. The outputs show the significant impact of learning on objective function values.

Practical implications

The proposed model and algorithm can be used for scheduling activities of small- and large-size real-world projects.

Originality/value

Based on the previous studies reviewed in this paper, one of the research gaps is the MSRCPSP with time-dependent resource capacities and requests. Therefore, this paper proposes a multi-objective model for the MSRCPSP with time-dependent resource profiles. Besides, the evaluation of learning effect on efficiency of workforces has not been studied sufficiently in the literature. In this study, the effect of learning on efficiency of workforces has been considered. In the scarce number of proposed models with learning effect, the researchers have assumed that the efficiency of workforces increases as they spend more time on performing a skill. To the best of the authors’ knowledge, the effect of learning from more efficient co-workers has not been studied in the literature of the RCPSP. Therefore, in this research, the effect of learning from more efficient co-workers has been investigated. In addition, a modified version of the NSGA-II algorithm is developed to solve the model.

Details

Journal of Modelling in Management, vol. 14 no. 2
Type: Research Article
ISSN: 1746-5664

Keywords

To view the access options for this content please click here
Article
Publication date: 29 January 2021

Hongwei Zhu, Zhiqiang Lu, Chenyao Lu and Yifei Ren

To meet the requirement of establishing an effective schedule for the assembly process with overall detection and rework, this paper aims to address a new problem named…

Abstract

Purpose

To meet the requirement of establishing an effective schedule for the assembly process with overall detection and rework, this paper aims to address a new problem named resource-constrained multi-project scheduling problem based on detection and rework (RCMPSP-DR).

Design/methodology/approach

First, to satisfy both online and offline scheduling, a mixed integer programming model is established with a weighted bi-objective minimizing the expected makespan and the solution robustness. Second, an algorithm that combines a tabu search framework with a critical chain-based baseline generation scheme is designed. The tabu search framework focuses on searching for a reasonable resource flow representing the execution sequence of activities, while the critical chain-based baseline generation scheme establishes a buffered baseline schedule by estimating the tradeoff between two aspects of bi-objective.

Findings

The proposed algorithm can get solutions with gaps from −4.45% to 2.33% when compared with those obtained by the commercial MIP solver CPLEX. Moreover, the algorithm outperforms four other algorithms in terms of both objective performance and stability over instances with different weighting parameters, which reveals its effectiveness.

Originality/value

The represented RCMPSP-DR considering the overall detection and rework is an extension of the scheduling problem for large-scale equipment. An effective algorithm is proposed to establish the baseline schedule and determine the execution sequence of activities for the assembly process, which is significant for practical engineering applications.

Details

Assembly Automation, vol. 41 no. 2
Type: Research Article
ISSN: 0144-5154

Keywords

To view the access options for this content please click here
Article
Publication date: 16 May 2016

Emad Elbeltagi, Mohammed Ammar, Haytham Sanad and Moustafa Kassab

Developing an optimized project schedule that considers all decision criteria represents a challenge for project managers. The purpose of this paper is to provide a…

Abstract

Purpose

Developing an optimized project schedule that considers all decision criteria represents a challenge for project managers. The purpose of this paper is to provide a multi-objectives overall optimization model for project scheduling considering time, cost, resources, and cash flow. This development aims to overcome the limitations of optimizing each objective at once resulting of non-overall optimized schedule.

Design/methodology/approach

In this paper, a multi-objectives overall optimization model for project scheduling is developed using particle swarm optimization with a new evolutionary strategy based on the compromise solution of the Pareto-front. This model optimizes the most important decisions that affect a given project including: time, cost, resources, and cash flow. The study assumes each activity has different execution methods accompanied by different time, cost, cost distribution pattern, and multiple resource utilization schemes.

Findings

Applying the developed model to schedule a real-life case study project proves that the proposed model is valid in modeling real-life construction projects and gives important results for schedulers and project managers. The proposed model is expected to help construction managers and decision makers in successfully completing the project on time and reduced budget by utilizing the available information and resources.

Originality/value

The paper presented a novel model that has four main characteristics: it produces an optimized schedule considering time, cost, resources, and cash flow simultaneously; it incorporates a powerful particle swarm optimization technique to search for the optimum schedule; it applies multi-objectives optimization rather than single-objective and it uses a unique Pareto-compromise solution to drive the fitness calculations of the evolutionary process.

Details

Engineering, Construction and Architectural Management, vol. 23 no. 3
Type: Research Article
ISSN: 0969-9988

Keywords

To view the access options for this content please click here
Article
Publication date: 23 September 2021

P. Raghuram and Mahesh Kumar Arjunan

This purpose of this study is to develop a simple framework for designing a warehouse incorporating lean principles. Multiple objectives like resource planning, material…

Abstract

Purpose

This purpose of this study is to develop a simple framework for designing a warehouse incorporating lean principles. Multiple objectives like resource planning, material handling, storage, inventory management, including internal and external logistics, are considered.

Design/methodology/approach

A design procedure to incorporate lean principles for designing a warehouse for a complex multi-model production line has been proposed. The preferred standards and factors affecting warehouse design, the inputs and outputs of process flow characteristics, are incorporated into the design. Current and future state value stream mappings are drawn to bring out the challenges in the value flow.

Findings

The framework for designing a lean warehouse have been implemented and validated in a heavy machinery manufacturer. This framework will ease the work of the future lean-based warehouse designers to apply simple step-by-step processes to achieve the goal with the nearest accuracy. The steps followed can be summarized as defining the lean processes, making the lean process as the design base, collecting inputs like stock-keeping unit master, inventory and space details, and building the lean warehouse design with the step-by-step processes.

Practical implications

Practical tips on warehouse design have been explained focusing on the part volume, quantity handled, inventory and throughput. This will assist the practitioners in designing a lean warehouse and leading to an improved operational performance.

Originality/value

A simplified design procedure for designing a lean warehouse, along with a real-time case study has been enumerated in detail. Effective use of space and resources with lean tools and techniques lead to better storage and picking efficiency resulting in an overall reduction in cost.

Details

International Journal of Productivity and Performance Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1741-0401

Keywords

To view the access options for this content please click here
Book part
Publication date: 20 January 2020

Ann M. Brewer

Abstract

Details

Careers: Thinking, Strategising and Prototyping
Type: Book
ISBN: 978-1-83867-210-2

To view the access options for this content please click here
Case study
Publication date: 20 January 2017

Richard E. Wilson

Colfax Corporation was a young, privately held collection of pump-manufacturing companies from the United States and Europe. Intending to go public, it was eager to find a…

Abstract

Colfax Corporation was a young, privately held collection of pump-manufacturing companies from the United States and Europe. Intending to go public, it was eager to find a story for investors of how it could grow at rates faster than its subsidiaries had historically grown in their home regions and core-customer industrial markets. This case describes a singular new-growth opportunity: selling Colfax solutions into state-owned petroleum enterprises in the Middle East at a time when these producers were straining to add capacity. Designing the optimal marketing system required Colfax to weigh a complex of issues, including global resource allocation and deployment, a process for customer-relationship building, and estimates for revenue streams versus investment outlays. The design process was, in short, far more than “sticking sales rep pins in the map.” Case readers are asked to think along with the Colfax global management team in deciding, “How much can we afford to risk our current income model in order to build new capacity in a new region in a new way?”

Understanding issues related to global B2B marketing channel strategy development, as well as complexities of entering unfamiliar new international markets such as Middle East oil and gas.

Details

Kellogg School of Management Cases, vol. no.
Type: Case Study
ISSN: 2474-6568
Published by: Kellogg School of Management

Keywords

To view the access options for this content please click here
Article
Publication date: 1 July 2011

Wang Wen Hui

The purpose of this paper is to argue that Bernoulli's “utility function solution to the St Petersburg paradox” was wrong and to find a new method to solve the paradox.

Abstract

Purpose

The purpose of this paper is to argue that Bernoulli's “utility function solution to the St Petersburg paradox” was wrong and to find a new method to solve the paradox.

Design/methodology/approach

This goal is attained through two ways: using Bernoulli's and Kramer's utility function to construct new paradoxes; and designing and implementing a new St Petersburg game which does not carry the effect of diminishing marginal utility.

Findings

In this paper, the author finds that Bernoulli's “utility function solution to the St Petersburg paradox” was wrong, and also finds a new model to solve the paradox, which is also a brand‐new model of estimates under uncertainty.

Research limitations/implications

Bernoulli put forward the diminishing marginal utility of currency and thus accordingly provided the utility function solution to solve the paradox. This paper indicates that the Bernoulli's utility function solution does not work. Thus, further research needs to be taken in several aspects: is the diminishing marginal utility of currency tenable? Does the marginal utility of currency decrease monotonically? Are concave utility functions represented by negative index functions which are widely used in theoretical study reasonable?

Practical implications

The paper proposes a brand‐new possible research idea and direction for economic theoretical researches based on uncertainty.

Originality/value

This paper proved the untenability of the utility function solution to solve the St Petersburg paradox for the first time and proposed the pioneering “risk adjustment model” of estimates under uncertainty.

Details

China Finance Review International, vol. 1 no. 3
Type: Research Article
ISSN: 2044-1398

Keywords

To view the access options for this content please click here
Article
Publication date: 17 September 2020

Beikun Zhang and Liyun Xu

The increasing energy shortage leads to worldwide attentions. This paper aims to develop a mathematical model and optimization algorithm to solve the energy-oriented…

Abstract

Purpose

The increasing energy shortage leads to worldwide attentions. This paper aims to develop a mathematical model and optimization algorithm to solve the energy-oriented U-shaped assembly line balancing problem. Different from most existing works, the energy consumption is set as a major objective.

Design/methodology/approach

An improved flower pollination algorithm (IFPA) is designed to solve the problem. The random key encoding mechanism is used to map the continuous algorithm into discrete problem. The pollination rules are modified to enhance the information exchange between individuals. Variable neighborhood search (VNS) is used to improve the algorithm performance.

Findings

The experimental results show that the two objectives are in conflict with each other. The proposed methodology can help manager obtain the counterbalance between them, for the larger size balancing problems, and the reduction in objectives is even more significant. Besides, the experiment results also show the high efficiency of the proposed IFPA and VNS.

Originality/value

The main contributions of this work are twofold. First, a mathematical model for the U-shaped assembly line balancing problem is developed and the model is dual foci including minimized SI and energy consumption. Second, an IFPA is proposed to solve the problem.

Details

Assembly Automation, vol. 40 no. 6
Type: Research Article
ISSN: 0144-5154

Keywords

To view the access options for this content please click here
Article
Publication date: 1 June 2000

George K. Chako

Briefly reviews previous literature by the author before presenting an original 12 step system integration protocol designed to ensure the success of companies or…

Abstract

Briefly reviews previous literature by the author before presenting an original 12 step system integration protocol designed to ensure the success of companies or countries in their efforts to develop and market new products. Looks at the issues from different strategic levels such as corporate, international, military and economic. Presents 31 case studies, including the success of Japan in microchips to the failure of Xerox to sell its invention of the Alto personal computer 3 years before Apple: from the success in DNA and Superconductor research to the success of Sunbeam in inventing and marketing food processors: and from the daring invention and production of atomic energy for survival to the successes of sewing machine inventor Howe in co‐operating on patents to compete in markets. Includes 306 questions and answers in order to qualify concepts introduced.

Details

Asia Pacific Journal of Marketing and Logistics, vol. 12 no. 2/3
Type: Research Article
ISSN: 1355-5855

Keywords

1 – 10 of over 82000