Industrial Engineering & Management

The thesis is a study on the optimization of scheduling of project development, with the problem stemming from Clash of Clans (COC)– a mobile phone-oriented network game developed by Supercell. Based on COC’s game environment, the author, through the analysis and evaluation of optimization tools, proposes the parameters setting that fits the game and provides the game strategy schemes needed by players, i.e. they can define the sequence and time arrangement of performing a game task via the optimization algorithm, so as to significantly reduce “redundant game time”, speed up the progress of games and obtain better game experience. The objective of the study is to analyze the needs of different players on the basis of becoming familiar with the game environment and to put forward optimal game strategy schemes in addition to meeting corresponding required conditions according to the game stage each player is in. Apart from establishing an operations research model that meet the goal of optimization on the foundation of game environment, the author adopts the Genetic Algorithm (GA) to undertake guiding search for feasible schemes that meet the required conditions so as to achieve optimal solutions. To explain the practical effects of the method in detail, the thesis will show and use the algorithm with a game case and demonstrate the effects and efficiency of the algorithm with a large quantity of data.

Nowadays due to high competition, organizations are looking to increase their market share but at the same time, they want quick return on investment (ROI). This article will define the basis of ROI and market share and try to find the relationship between them. At the end we will be able to answer the question “Is it Possible to Maximize Return on Investment and Achieve Adequate Market Share at the same time?”

With the inexorability of globalization and open trade system, there has been extension of large business with an increase in the outsourcing of parts and services especially in the apparel sector. Increasing in number, the apparel industries confront dormant competition and need to emphasize on some technical key points to be fortitude. Purchasing and its associated functions are the eminent fields playing important role in this connection as it is most decisive and most of the production cost and time are spent regard to those. As for trading, apparel sector products normally categorize into two - push and pull while pull products are executed in anticipation of the customer order and push products are initiated according to customer order. It engenders dealings with risk and cause more investment which may incur a loss to the industries because of any faltering decision. Appropriate supplier and supply quantity selection triggers the probably of success as other parameters evolve by these and hence they are most important and can reduce risk if it can be handled combined for several products. Using fuzzy-TOPSIS and MCGP, the paper determines the joint (push and pull) amount to take from each supplier based on their performance ranking on selected criteria considering budget, delivery, demand and supply constraints. The result generated solving a LP model formed on the basis of opportunity and threats. The model is solved by LINDO system. The strength of presenting approach is its practical applicability and ability to provide solution under partial or lack of quantitative information and in joint order handling.

Production planning, which allows the manufacturer to efficiently manage all production activities, is a major issue in manufacturing/processing industries. This study considers a medium-term production planning problem, in which a producer receives several periodic orders from multiple retailers at the beginning of the planning horizon. Given the limit in production capacity, the producer must reject some orders under the profit maximization principle, while considering multiple and inseparable orders, backlogging policy, and capacity limitation of the plant. Therefore, the producer faces two issues, namely, (a) which orders the producer should accept, and (b) how to allocate the products to the retailers. To solve these problems, we propose a multiple-period production plan in the form of an integer program. Theoretical development with numerical examples is provided. The results have shown that this study can help producers deal with a more realistic environment and derive useful product delivery information.

In the article the question on development the criterion for comparison of two variants of realization of trilateration method of acoustic location has been considered. It is shown, that upon fulfillment of some condition and sufficiently low level of noises in the signal the choice of the signal strength measuring techniques of trilateration method of location can be preferable.

In the traditional production lines such as assembly lines, each worker is usually assigned to a particular fixed position, and the speed of performing the task decreases until the worker masters the assigned work. However, when an imbalance in the speeds of the workers exists, any given worker can delay the overall work on the production line, and the production rate of the particular line will also decrease. To avoid this problem, the “Self-Balancing Production Line” was introduced. In this type of production line, each worker is assigned work dynamically so they can keep the production line balanced while satisfying the specific conditions. A previous paper studying worker learning has been published. When a worker learns, the speed of the worker can be increased. In that paper, the authors analyzed the conditions with and without passing and claimed that if passing is allowed, self-balancing of a production line can be achieved. However, even if the initial sequence is slowest to fastest (this is the best sequence for self-balance in the previous paper) and if passing is allowed, much more time is required to balance some conditions of speed and degree of learning (we call this the learning rate). Therefore, a new policy for rearranging workers that changes the sequence before passing should be considered for rapid balance of the production line. In this paper, the policy for rearranging workers that changes the sequence being learned is proposed, and to verify the policy, numerical experiments are performed under various conditions of speed and learning rate.