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The purpose of this paper is to find the most efficient assembly line balancing solution across many heuristic line balancing methods, in assistance with a developed computer program.

In this paper, assembly line balancing problem was analyzed using t-shirt and knitted pants data. A computer program using MATLAB software for the solution of assembly line balancing problems has been developed. In this study, following heuristic assembly line balancing methods were applied: Hoffman method; position weight method; COMSOAL method; and Kilbridge and Wester method. A MATLAB program has been developed by taking into account of theoretical solution of all these methods. Later the program is developed further by analyzing solutions made manually and is made to verify the developed program.

Pre-studies which were conducted in order to decide which programming language would be the best choice for line balancing methods’ application came out with the result that MATLAB, from between C, C++, C# and Java, would be the best software choice. The main reason for this choice is that MATLAB is a powerful matrix operation software with a powerful user interface designing tool and has the tools to make development program to be used universally in every computer.

When the researches were investigated, it is clearly seen that, this study is the first research on using computer program for solving assembly line balancing problem.

Construction resources are often limited, and there is a need to ensure resources are carefully allocated to avoid resource wastage and/or project delay. While mathematical and heuristic models were developed to resolve the conflicts between activities, none of them has been proven to be totally satisfactory. The aim of this paper is to explore this.

In this paper, a novel heuristic method known as a pull‐driven approach (PDA) is proposed; and this approach encourages a lean consideration of resource supply and partnering between activities. Two case studies are presented to illustrate how PDA can be applied. A comparison with another heuristic approach, namely the ranked positional weight method is conducted to illustrate the efficiency of the proposed approach.

Using the PDA approach, all the activities strive to find matching partners to pull resources to their sides. The resources are, therefore, no longer passively pushed to a single activity with high ranking but a combination of activities that can demonstrate their superiority in resource utilisation will actively win the necessary resources.

This approach has an ability to deal with intermittent activities and locate the lean (no‐waste) supply level of each resource.

This paper briefly reviews the assembly line balancing techniques developed over the last 30 years. It attempts to establish the direction of research, to identify unexplored areas with potential for study and recommends future courses of action.

Brings knowledge of assembly line balancing algorithms into the clothing industry. Uses an already published algorithm to solve a particular problem, obtained from a British clothing manufacturer. Identifies optimum solutions to the problem for the situation when each operative is assumed to be equally productive and when differences in operator productivity are allowed for. In the case of equal productivity of operators three optimum solutions to the problem were identified. When varying operator productivity was allowed for, two optimum solutions to the problem were identified. The identification of these multiple optimum solutions allows the line balancer increased flexibility in the choice of particular solutions.

This article aims to suggest to managers involved in re‐engineering projects a method to assess the feasibility of manufacturing re‐insourcing.

At first, an analysis of the textile sector is carried out. Subsequently, a methodology is described, able to assess the feasibility of manufacturing re‐insourcing. As a case study, a high production shop is then proposed and sized for the quick response requirements of a company producing young apparel lines on behalf of third parties. Finally, an economic evaluation is carried out in order to assess the profitability of the re‐insourcing strategy.

A methodology which can aid managers to assess the feasibility of manufacturing re‐insourcing in re‐engineering programs is proposed.

The proposed methodology is original.

The purpose of the study is to fill a gap in the literature on mathematical production planning (joint balancing and sequencing) in the fashion industry. It considers in particular situations of mass customization, made-to-measure or small lot sizes.

The paper develops a mathematical model based on product options and attributes instead of fixed variants. It proposes an easy-to-use genetic algorithm to solve the resulting optimization problem. Functionality and performance of the algorithm are illustrated via a computational study.

An easy-to-implement, yet efficient algorithm to solve the multi-objective implementation of a problem structure that becomes increasingly relevant in the fashion industry is proposed. Implementation of the algorithm revealed that the algorithm is ideally suited to generate significant savings and that these savings are impervious to problem and thus company size.

The solutions from the algorithm (Pareto-efficient frontier) offer decision-makers more flexibility in selecting those solutions they deem most fitting for their situation. The computational study illustrates the significant monetary savings possible by implementing the proposed algorithm to practical situations.

In contrast to existing papers, for the first time, to the best of the author’s knowledge, the focus of the joint balancing and sequencing approach has been applied in the fashion instead of the automotive industry. The applicability of the approach to specific fields of the fashion industry is discussed. An option and attributes-based model, rarely used in general assembly line sequencing per se, is used for more flexibility in representing a diverse set of model types.

The purpose of this paper is to examine the usefulness of fusion as a means of improving the precision of automated opinion detection.

Five system fusion methods are proposed and tested using runs submitted by the Text REtrieval Conference (TREC) Blog06 participants as input. The methods include a voting method, an inverse rank method (IRM), a linear‐normalised score method and two weighted methods that use a weighted IRM score to rank the document.

Mean average precision (MAP) is used as an indicator of the performance of the runs in this study. The best system fusion method achieves a 55.5 percent higher MAP result compared with the highest MAP result of any individual run submitted by the Blog06 participants. This equates to an increase in detection of 2,398 relevant opinion documents (21 percent).

System fusion can be used to improve upon the results achieved by existing individual opinion detection systems. On the other hand, multiple opinion detection approaches can be combined into one system and fusion used to combine the results to build in diversity. Diversity within fusion inputs can increase the improvements achieved by fusion methods. The improved output from a diverse opinion detection system will then contain a higher number of relevant documents and reduce the incidence of high‐ranking non‐relevant documents and low‐ranking relevant documents.

The fusion methods proposed in this study demonstrate that simple fusion of opinion detection systems can improve performance.

Three-parameter interval grey numbers (TPIGNs) have been extensively studied as an extended form of interval numbers. However, most existing TPIGN multi-attribute decision-making methods only consider the similarity of positions, ignore the similarity of developmental directions and focus primarily on static evaluation. To address these limitations, in this study, the authors propose a dynamic technique for order preference by similarity to an ideal solution (TOPSIS) based on modified Jaccard similarity and angle similarity for TPIGNs.

First, the authors extend Jaccard similarity to a TPIGN environment to represent positional similarity. A simple example is provided to illustrate the limitations of the traditional Jaccard similarity. Then, the authors introduce an angle similarity measure to represent developmental directional similarity. Finally, a dynamic TOPSIS model is constructed by incorporating time-series data into conventional two-dimensional static data. Stage weights are obtained by an objective function designed to maximize the amount and minimize the fluctuation of decision information. A quadratic weighting method is adopted to derive the overall evaluation value of alternatives.

To evaluate the effectiveness of the proposed method, this study takes the pre-assessment of ice disaster and the selection of cooperative enterprises as examples. The authors then provide the results of comparative and sensitivity analyses, which demonstrate the effectiveness and flexibility of the proposed method.

The proposed TOPSIS method in a TPIGN environment can take a more holistic and dynamic perspective for decision-making, which helps mitigate the limitations of single-perspective or static evaluations.

Term position information, as provided in some Boolean systems in the form of field restriction and term proximity, is reviewed and its value assessed. Non‐Boolean retrieval in the form of the ranked output experiment has not so far used term position information but has concentrated on schemes of term weighting. The use of term proximity devices is proposed here by analogy with Boolean techniques and seven algorithms are devised to incorporate the ideas of sentence matching, proximate terms, term order specification and term distance computations. It is hypothesised that term position will act as a precision device. A new search experiment is then described in which a test collection is processed into sentences and then output ranking using term position is obtained. Results are given for five algorithms compared against quorum searching as the benchmark. The best result increased the precision ratio by 18% and used proximate matching term pairs in sentences plus a distance component.

The purpose of this study is to first investigate the efficiency of the most commonly used performance measures for minimizing the number of workstations (NWs) in approaches addressing simple assembly line balancing problem (SALBP) for both straight and U-shaped line, and second to provide a comparative evaluation of 20 constructive heuristics to find solutions to the SALBP-1.

A total of 200 problems are solved by 20 different constructive heuristics for both straight and U-shaped assembly line. Moreover, several comparisons have been made to evaluate the performance of constructive heuristics.

Minimizing the smoothness index is not necessarily equivalent to minimizing the NWs; therefore, it should not be used as the fitness function in approaches addressing the SALBP-1. Line efficiency and the idle time are indeed reliable performance measures for minimizing the NWs. The most promising heuristics for straight and U-shaped line configurations for SALBP-1 are also ranked and introduced.

Results are expected to help scholars and industrial practitioners to better design effective solution methods for having the most balanced assembly line. This study will further help with choosing the most proper heuristic with regard to the problem specifications and line configuration.

There is limited research assessing the efficiency of the common objectives for SALBP-1. This study is among the first to prove that minimizing the workload smoothness is not equivalent to minimizing the NWs in SALBP-1 studies. This work is also one of the first attempts for evaluating the constructive heuristics for both straight and U-shaped line configurations.