Ghorbanali Mohammadi ¹

Affiliations
1 Department of Industrial Engineering, Shahid Bahonr University Kerman, Kerman, 7618891167, IR

Abstract

The fuzzy scheduling is a new approach presented in this paper. In classic scheduling, it was assumed that the machines are always available. So, no maintenance time was considered for calculations. Also, assumed that all given times are exact and there is no uncertainty, however in the real word accurate calculation is impossible and always faced with uncertainty. Therefore, scheduling calculations would not be accurate and an optimal solution would not be reached. In this study, rate-modifying activity time considered as the fuzzy number and the optimal solution was calculated in uncertainty condition. A novel type of fuzzy scheduling model is presented. A ROG algorithm for ranking fuzzy numbers was introduced and example was solved to show the effectiveness of the proposed approach.

Keywords

Fuzzy Algorithm, Machine Scheduling, Job Scheduling Rate-modifying Activity, Single Machine

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Ghorbanali Mohammadi ¹

Affiliations
1 Industrial Engineering Department, College of Engineering, Shahid Bahonar University of Kerman, IR

Abstract

Time-cost trade-off analysis is one of the most important aspects of industrial project planning and control. There are trade-offs between time and cost to complete the activities of a project; in general, the less expensive the resources used, the longer it takes to complete an activity. Existing methods for time-cost trade-off problems focus on using heuristics or mathematical programming. These methods, however, are not efficient enough to solve large scale CPM problems. This paper presents a Multi-Objective Genetic Algorithm (MOGA) approach to time-cost trade-off problems (TCTP). Finding optimal decisions is difficult and time-consuming considering the numbers of permutations involved. This type of problem is NP-hard, hence attainment of IP/LP solutions, or solutions via Total Enumeration (TE) is computationally prohibitive. The MOGA approach searches for locally Pareto-optimal or locally non-dominated frontier where simultaneously optimization of time-cost is desired. The application of the proposed algorithm is demonstrated through an example project a real life case. The results illustrate the promising performance of the proposed algorithm.

Keywords

Time-cost Trade-off, Genetic Algorithms, Project Management

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Sajjad Najafi ¹, Vahid Majazi Dalfard ², Ghorbanali Mohammadi ³

Affiliations
1 Department of Industrial Engineering, Shahed University, Tehran, IR
2 Islamic Azad University, Qazvin Branch, Faculty of Industrial and Mechanical Engineering, Qazvin, IR
3 Department of Industrial Engineering, Shahid Bahonr University Kerman, Kerman, 7618891167, IR

Abstract

In this paper, the locating problem was studied by considering a network of nodes and edges, and also two types of facilities which were defined for locating on nodes. It was assumed that there were three types of consumers, which were classified according to their demands. The first and the second types of them referred to one facility of the first or the second, but the third type of consumers needed the two facilities-the first and the second. These consumers according to their distance to the facilities based on a specified probability, referred to the facilities and solved their problems. Considering the existence of competitors in the market, the aim of this issue is to maximize market share for the new facilities. To solve the problem the hybrid genetic algorithm was used.

Keywords

Consumer, Market, Trip, Network, Hybrid Genetic Algorithm, Logit Function

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