Multicriteria scheduling using fuzzy theory and tabu search

Abstract

Scheduling problems are frequently encountered in manufacturing systems. The results of job scheduling can have a great impact on the throughputs of systems. To maintain a high level of productivity of the systems, many objectives have to be taken into account simultaneously while evaluating the results of a scheduling arrangement. Unfortunately, in the high-dimension environment of considering these objectives, the performance evaluation over the criteria of interest becomes rather vague. Thus, it is very di cult to apply the traditional numerical methods to construct the models, though the measurement of these may not be fully compatible with the criteria of the scheduling problems. In this paper, the linguistic values of fuzzy set theory are introduced to evaluate each criterion and to represent its relative weight for the schedules of a multicriteria environment. The basic operations for the triangular fuzzy numbers and the calculations for obtaining the ranking of each aggregated linguistic evaluation for the quality of the schedule are explained clearly. According to the complex property of scheduling problems, a heuristic approach of tabu search is applied to solve the problems. The basic mechanism and spirits of the tabu search are also interpreted here. The overall procedure of the proposed approach is addressed by a numerical example. The aim is to propose an approach that can more easily apply the multicriteria technique.

A hybrid heuristic approach to minimize number of tardy jobs in group technology systems

“…Lee et al. () consider multiple criteria for scheduling a single machine in a flow shop environment including minimizing the number of tardy jobs. They use the algorithm developed by Moore () to solve the problem.…”

“…Moore (1968) develops an algorithm for scheduling multiple jobs on a single machine with an objective to minimize the number of tardy jobs. Lee et al (2002) consider multiple criteria for scheduling a single machine in a flow shop environment including minimizing the number of tardy jobs. They use the algorithm developed by Moore (1968) to solve the problem.…”

Analysis of priority mix planning for the fabrication of semiconductors under uncertainty

“…The numbers that satisfy the three requirements are called fuzzy numbers, and there are two most commonly used fuzzy numbers: the trapezoidal fuzzy number and the triangular fuzzy number [4,8,[17][18][19]. A fuzzy number B in the universe of discourse U may be characterized by a trapezoidal distribution parametrized by a quadruple (l, a, b, u), as shown in Fig.…”

A fuzzy logic based production scheduling/rescheduling in the presence of uncertain disruptions

“…Real-life production scheduling, in essence, involve multi-criteria to be considered simultaneously. Different production scheduling problems have been treated using fuzzy multi-criteria decision making methods, for example, scheduling of single machine [2,13,16], job shop [25,5,8], flow shop [19,12], and so on. Slany [26] presented a method of formalising imprecise relative importance of fuzzy constraints and its application to multiple criteria steelmaking scheduling.…”