In the present competitive world, facility location is an important aspect of the supply chain (sc) optimization. It involves selecting specific locations for facility construction and allocation of the distribution channel among different SC levels. In fact, it is a strategic issue which directly affects many operational/tactical decisions. Besides the accessibility, which results in customer satisfaction, the present paper optimizes the establishment costs of a number of distribution channels by considering their proximity to the stock market of the goods they distribute, and proposes mathematical models for two objective functions using the set covering problem. Then, two objective functions are proposed into one through the ε-constraint method and solved by the metaheuristic Genetic Algorithm (GA). To test the resulted model, a smaller scale problem is solved. Results from running the algorithm with different ε-values show that, on average, a 10% increase in ε, which increases the value of the second objective function - distance covered by customers will cause a 2% decrease in the value of the first objective function including the costs of establishing distribution centers). The repeatability and solution convergence of the two-objective model presented by the GA are other results obtained in this study.
This paper performs an investigation to rank different strategies in an engineering firm in Iran. The proposed study designs a questionnaire and distributes it among all experts who worked for a firm in engineering field named Kara Sazeh Matin. The study first determines four key strategies for development of firm’s objectives including improvement in buy/sell system and marketing planning, financial and cost management, human resources management and technology management. The study ranks these attributes based on fuzzy analytical hierarchy process (FAHP) and technique for order of preference by similarity to ideal solution (TOPSIS) in fuzzy format. The results indicate the firm must take over one of the well-known construction firms to develop its operations.