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With the growing demand for Ready-To-Wear outfits especially in African textile prints, the currently used European, American and Asian garment sizing systems seems unsuitable for the Nigerian garment industry where customer's choose clothing item not only due to fit in terms of body measurements but also the dress culture, style, preference and some other implicit requirements. This study aims to develop a size chart for different styles of trousers worn by Nigeria male population. Anthropometric data of 500 customers were taken in a natural random process and from stable tailoring establishments. The data was analysed using descriptive statistics and the fuzzy clustering methodology (FCM) was used as a suggestive approach which describes subjectivity in customer preferences. Analysis of the FCM output shows that the number of individual measurements with misfit has no significant difference (F estimated = 1.119, p-value=0.375 and F critical = 2.866) across cluster. The percentages of misfit were 38.0, 23.4, 31.6, 31.4 and 3.8% for hip measurement, length, waist, thigh and bottomgirth respectively. The developed sizing system which reflects subjectivity in customer's selection of trouser may also enhance both producer and retailer's production and replenishment policy.

The long-standing issue of non-pre-emption in ‘multi-period’ production/maintenance (P/M) scheduling has always been a challenge and this has been the focus of many researchers. Recently, the Contiguous-Cells Transportation Model (CCTM) was proposed to address this problem. However, the CCTM is limited to non-pre-emptive P/M scheduling decision situations where only one objective is of concern. The multiple objective non-pre-emptive P/M scheduling are encountered more frequently in the real world than the single objective case. This study proposed the Multi-Objective Contiguous-Cells Transportation Model (MOCCTM) and the solution procedure for handling multi-objective cases of non-pre-emptive production/maintenance scheduling. The variables and parameters of the CCTM were adopted with modifications to cater for the multi-objective requirements. A composite multiple-objective function was formulated by employing multi-objective optimisation techniques of assigning weights to objectives and normalisation of objectives. An algorithm similar to the conventional least cost method was developed for the solution of the MOCCTM. A bi-objective non-pre-emptive maintenance scheduling problem of 5 production machines across an operation and maintenance planning horizon of 10 periods was used to demonstrate the application of the MOCCTM. The MOCCTM is a good approach to solving multi-objective P/M scheduling problems in a non-pre-emptive environment.

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