Fashion Supply Chain Optimization: A Linear Programming Model

Fashion supply chain management is challenging due to demand uncertainty, short product life, fierce global competition, and increasing expectations such as product diversity and keeping pace with the current and emerging trends. In this paper, a brief review of the published works in the field of fashion and clothing supply chain is given and an integrated linear model is presented to minimize a fashion brand’s costs, including production and logistics costs, enabling the firm to make better decisions with regard to its production and replenishment policies and responding in a reasonable time to customers demands for various designed items. We show that our model can successfully account for complex structure of the supply chain consisting of designer, manufacturers, distributors, and stores. The model is validated using the General Algebraic Modelling System (GAMS) with the data collected from an Iranian fashion brand.

Interactive Multiple Objective Asset Allocation

Portfolio efficiency and suitability are two important goals in the asset allocation processing involving a financial advisor and clients. The Analytic Hierarchy Process (AHP) technique is employed as a framework to address an investor's multiple investment objectives. Questionnaires, GAMS (General Algebraic Modelling System) programs and spreadsheet models are developed to facilitate the communications between the financial advisor and investor.

Interactive Multiple Objective Asset Allocation

Portfolio efficiency and suitability are two important goals in the asset allocation processing involving a financial advisor and clients. The Analytic Hierarchy Process (AHP) technique is employed as a framework to address an investor's multiple investment objectives. Questionnaires, GAMS (General Algebraic Modelling System) programs and spreadsheet models are developed to facilitate the communications between the financial advisor and investor.

Optimal Biomass Transportation Model

The transportation represents a key proportion of the operational cost for the biomass industries worldwide. As biomasses are mainly carried by trucks for parts of the transportation, the focus of this paper is on the transport of treated and untreated biomass (rice husk, empty fruit bunch, and woody biomass) by large, medium and small trucks. The objectives were to formulate biomass transportation model for transporting treated and untreated biomass resources and to obtain optimal result for selecting the best transportation mode. By screening of biomass types, locations for treated and untreated biomass resources and screening of suitable transportation mode used, the important model parameters were obtained and linear programming for minimizing overall transportation costs was formulated. General Algebraic Modelling System (GAMS) software was used to solve the optimization formulations. From the optimization result obtained by using GAMS, large truck was selected to be the best transportation mode for treated, untreated and hybrid biomass since it showed minimal overall transportation cost.

Application of BARON Solver for Solution of Cost Based Unit Commitment Problem

This paper presents the solution to cost-based unit commitment (CBUC) problem with and without ramp rate limits of thermal power plants using general algebraic modelling system (GAMS) with BARON solver. The BARON solver in GAMS environment takes care of different units and system constraints to find an optimal solution. To validate the effectiveness of the proposed GAMS solution, simulations have been performed on six different systems consisting of 10-units, 20-units, 40-units, 60-units, 80-units and 100-units, respectively. The analysis also includes the valve-point loading along with the ramp rate limits of thermal units. Results obtained with BARON solver in GAMS have been compared with other approaches available in literature. Comparative analysis shows that the performance of GAMS is better as compared to other existing techniques in terms of operating cost obtained and satisfaction level of constraints.