The problem of scheduling is an area that has attracted a lot attention from researchers for many years. Its goal to optimize resources in the system. lecturer’s assigning task example timetabling problem, class scheduling. This study introduces mathematical model assign constrained tasks (the time and required skills) university lecturers. Our capable generating calendar maximizes faculty expe...

This paper uses the L1−norm and the concept of the non-dominated vector, topropose a method to find a well-dispersed subset of non-dominated (WDSND) vectorsof a multi-objective mixed integer linear programming (MOMILP) problem.The proposed method generalizes the proposed approach by Tohidi and Razavyan[Tohidi G., S. Razavyan (2014), determining a well-dispersed subset of non-dominatedvectors of...

This note is motivated by the similarity between multiobjective programming (MOP) and bargaining theory. It uses the known MOP concepts to establish two new bargaining results: (1) the efficiency of KalaiSmorodinsky (KS) and Nash (NA) solutions for large classes of bargaining problems can be refined to the sharper concept of proper efficiency; (2) the independence of irrelevant alternatives (II...

HLP (hub location problem) tries to find locations of hub facilities and assignment of nodes to extended facilities. Hubs are facilities to collect, arrange, and distribute commodities in telecommunication networks, cargo delivery systems, etc. Hubs are very crucial and their inaccessibility impresses on network whole levels. In this paper, first, total reliability of the network is defined bas...

Most optimization problems naturally have several objectives, usually in conflict with each other. The two or three objective functions are referred to as Multi-Objective Problems (MOP). However, many real-world applications often involve four more which commonly recognized many-objective (MaOP). Multi and algorithms a great application engineering science. This study addresses complete updated...

This paper improves a recently developed multi-objective particle swarm optimizer (D2MOPSO) that incorporates dominance with decomposition used in the context of multi-objective optimization. Decomposition simplifies a multi-objective problem (MOP) by transforming it to a set of aggregation problems, whereas dominance plays a major role in building the leaders' archive. D2MOPSO introduces a new...

A very useful multi-objective technique is goal programming. There are many methodologies of goal programming such as weighted goal programming, min-max goal programming, and lexicographic goal programming. In this paper, weighted goal programming is reformulated as goal programming with logarithmic deviation variables. Here, a comparison of the proposed method and goal programming with weighte...