Ching‐Jong Liao and Chih‐Hsiung Shyu
Almost all inventory models assume that lead time is prescribed andthus is not subject to control. In many practical situations, however,lead time is controllable; that is, lead…
Abstract
Almost all inventory models assume that lead time is prescribed and thus is not subject to control. In many practical situations, however, lead time is controllable; that is, lead time can be shortened, at the expense of extra costs, so as to improve customer service, reduce inventory investment in safety stocks, and improve system responsiveness. Although some authors recognise the advantage of short lead time and suggest that it should be considered a variable for management to control instead of a given, there is a lack of a suitable inventory model for determining the optimal lead time. A probabilistic inventory model in which the lead time is a decision variable is presented. It is assumed that the demand follows normal distribution and the lead time consists of n components each having a different cost for reduced lead time. The objective is to determine the lead time that minimises the sum of the expected holding cost and the additional cost.
Details
Keywords
Critical‐ratio technique is a common approach used to identify thenext job to run on a machine. Recently, an alternative procedure, knownas the contingent critical‐ratio…
Abstract
Critical‐ratio technique is a common approach used to identify the next job to run on a machine. Recently, an alternative procedure, known as the contingent critical‐ratio technique, has been proposed and proved to be superior to the conventional critical‐ratio rule. Examines the logic of the contingent critical‐ratio technique and proposes a new procedure. Experimental results show that the new procedure performs better than both the contingent critical‐ratio and the conventional critical‐ratio techniques.
Details
Keywords
Ching‐Jong Liao and Chien‐Yuan Kao
Suggests that with the shortage of nursing personnel, hospital administrators have to pay more attention to the needs of nurses to retain and recruit them. Also asserts that…
Abstract
Suggests that with the shortage of nursing personnel, hospital administrators have to pay more attention to the needs of nurses to retain and recruit them. Also asserts that improving nurses’ schedules is one of the most economic ways for the hospital administration to create a better working environment for nurses. Develops an algorithm for scheduling nursing personnel. Contrary to the current hospital approach, which schedules nurses on a person‐by‐person basis, the proposed algorithm constructs schedules on a day‐by‐day basis. The algorithm has inherent flexibility in handling a variety of possible constraints and goals, similar to other non‐cyclical approaches. But, unlike most other non‐cyclical approaches, it can also generate a quality schedule in a short time on a microcomputer. The algorithm was coded in C language and run on a microcomputer. The developed software is currently implemented at a leading hospital in Taiwan. The response to the initial implementation is quite promising.
Details
Keywords
Wen‐Jinn Chen and Ching‐Jong Liao
Machine maintenance is essential in many industries. How to schedule maintenance becomes especially important when achieving high shop performance is desired. This paper aims to…
Abstract
Purpose
Machine maintenance is essential in many industries. How to schedule maintenance becomes especially important when achieving high shop performance is desired. This paper aims to consider the maintenance scheduling problem in a company where different maintenance situations exist.
Design/methodology/approach
The company, which is famous in South East Asia, specializes in the manufacturing of textiles such as polypropylene and chemical chip. In this paper an algorithm is presented, for five specific situations, for the company to minimize the number of tardy jobs.
Findings
Owing to machine overload in 24‐hour production, machine breakdowns usually occur in the shop. There is an urgent need for the company to derive a procedure that will incorporate the maintenance into the schedule to reduce the machine breakdown. Computational results have showed that the proposed algorithm outperforms the current method with an average improvement of 32.5 percent, although the actual average improvement is somewhat lower partly because some jobs are unexpectedly cancelled or changed.
Practical implications
This proposed algorithm is appropriate not only for the studied company, but for those companies where maintenance has to be operated one or several times a month and the maintenance time is so significant that it cannot be ignored.
Originality/value
Provides an algorithm to aid in the maintenance scheduling problem.
Details
Keywords
Kuo-Jui Wu, Ching-Jong Liao, MingLang Tseng and Kevin Kuan-Shun Chiu
The purpose of this paper is to enhance the understanding of sustainable supply chain management (SSCM) and provide a comprehensive and quantitative method to assess performance…
Abstract
Purpose
The purpose of this paper is to enhance the understanding of sustainable supply chain management (SSCM) and provide a comprehensive and quantitative method to assess performance.
Design/methodology/approach
The study applied interval-valued triangular fuzzy numbers associated with grey relational analysis to improve the insufficient information and overcome the incomplete system under uncertainty.
Findings
The findings support the argument that the triple bottom line is insufficient to cover the entire concept of SSCM; in particular, the aspects of operations, stakeholders and resilience have not been addressed in previous studies.
Research limitations/implications
The results reveal that the triple bottom line concept is insufficient to illustrate the principles of SSCM and to provide an extensive basis for theory development. The aspects and criteria considered in the study only relate to the studied company and may need to be reviewed when applied to other industries.
Practical implications
The methodology and findings of the study demonstrate the core applications of criteria ranking and identify priority areas that utilize less investment but that may maintain the studied company’s current performance. Suggestions for the prioritization of criteria to enhance SSCM performance are provided.
Originality/value
The present study provides three valuable contributions. First, it adopts collaboration theory to furnish a theoretical foundation for SSCM. Second, the proposed hybrid method is able to overcome uncertainty and subsequently evaluate SSCM while utilizing incomplete and imprecise information. Third, the evaluation provides significant results for consideration in decision making by the studied company.
Details
Keywords
Sahar Tadayonirad, Hany Seidgar, Hamed Fazlollahtabar and Rasoul Shafaei
In real manufacturing systems, schedules are often disrupted with uncertainty factors such as random machine breakdown, random process time, random job arrivals or job…
Abstract
Purpose
In real manufacturing systems, schedules are often disrupted with uncertainty factors such as random machine breakdown, random process time, random job arrivals or job cancellations. This paper aims to investigate robust scheduling for a two-stage assembly flow shop scheduling with random machine breakdowns and considers two objectives makespan and robustness simultaneously.
Design/methodology/approach
Owing to its structural and algorithmic complexity, the authors proposed imperialist competitive algorithm (ICA), genetic algorithm (GA) and hybridized with simulation techniques for handling these complexities. For better efficiency of the proposed algorithms, the authors used artificial neural network (ANN) to predict the parameters of the proposed algorithms in uncertain condition. Also Taguchi method is applied for analyzing the effect of the parameters of the problem on each other and quality of solutions.
Findings
Finally, experimental study and analysis of variance (ANOVA) is done to investigate the effect of different proposed measures on the performance of the obtained results. ANOVA's results indicate the job and weight of makespan factors have a significant impact on the robustness of the proposed meta-heuristics algorithms. Also, it is obvious that the most effective parameter on the robustness for GA and ICA is job.
Originality/value
Robustness is calculated by the expected value of the relative difference between the deterministic and actual makespan.