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The traveling purchaser problem (TPP) has gained attention in academics to deal with different variants in real business world. This study aims to study a green TPP with quantity discounts and soft time windows (TPPQS), in which a firm needs to purchase products from a set of available markets and deliver the products to a set of customers.

Vehicles are available to visit the markets, which offer products at different prices and with different quantity discount schemes. Soft time windows are present for the markets and the customers, and earliness cost and tardiness may incur if a vehicle cannot arrive a market or a customer within the designated time interval. The environmental impact of transportation activities is considered. The objective of this research is to minimize the total cost, including vehicle-assigning cost, vehicle-traveling cost, purchasing cost, emission cost, earliness cost and tardiness cost, while meeting the total demand of the customers and satisfying all the constraints. A mixed integer programming (MIP) model and a genetic algorithm (GA) approach are proposed to solve the TPPQS.

The results show that both the MIP and the GA can obtain optimal solutions for small-scale cases, and the GA can generate near-optimal solutions for large-scale cases within a short computational time.

The proposed models can help firms increase the performance of customer satisfaction and provide valuable supply chain management references in the service industry.

The proposed models for TPPQS are novel and can facilitate firms to design their green traveling purchasing plans more effectively in today’s environmental conscious and competitive market.

This paper seeks to construct a model for inventory management for multiple periods. The model considers not only the usual parameters, but also price quantity discount, storage and batch size constraints.

Mixed 0‐1 integer programming is applied to solve the multi‐period inventory problem and to determine an appropriate inventory level for each period. The total cost of materials in the system is minimized and the optimal purchase amount in each period is determined.

The proposed model is applied in colour filter inventory management in thin film transistor‐liquid crystal display (TFT‐LCD) manufacturing because colour filter replenishment has the characteristics of price quantity discount, large product size, batch‐sized purchase and forbidden shortage in the plant. Sensitivity analysis of major parameters of the model is also performed to depict the effects of these parameters on the solutions.

The proposed model can be tailored and applied to other inventory management problems.

Although many mathematical models are available for inventory management, this study considers some special characteristics that might be present in real practice. TFT‐LCD manufacturing is one of the most prosperous industries in Taiwan, and colour‐filter inventory management is essential for TFT‐LCD manufacturers for achieving competitive edge. The proposed model in this study can be applied to fulfil the goal.

Most industries have become increasingly competitive nowadays, and a good supply chain relationship is essential for a company to survive and to acquire reasonable profit. Therefore, supplier selection is very important. The purpose of this paper is to propose a novel model for evaluating the performance of suppliers.

A supplier performance evaluation model based on analytic hierarchy process (AHP) and data envelopment analysis (DEA) is constructed. DEA is applied first to evaluate quantitative factors, and the results are transformed into pairwise comparison values for AHP analysis. Qualitative factors are also evaluated through AHP analysis, and a final ranking of suppliers can be obtained by combining the quantitative and qualitative results.

The proposed model can be applied to evaluate and select the most appropriate integrated circuit packaging company for outsourcing. With the incorporation of experts' opinions and the consideration of qualitative and quantitative factors, the model can provide a both subjective and objective supplier performance ranking.

The proposed model can be tailored and applied to supplier evaluation and selection in other industries.

Although many models are available for supplier evaluation, this paper considers both the subjective and objective performance characteristics simultaneously in the evaluation process.