This paper proposes a multi-objective Slime Mould Algorithm (MOSMA), variant of the recently-developed (SMA) for handling optimization problems in industries. Recently, problems, several meta-heuristic and evolutionary techniques have been suggested community. These methods tend to suffer from low-quality solutions when evaluating (MOO) than addressing objective functions identifying Pareto opt...

Although significant private investment is absorbed in different sectors of power systems, transmission sector is still suffering from appropriate private investment. This is because of the pricing policies of transmission services, tariffs, and especially for investment risks. Investment risks are due to the uncertain behaviour of power systems that discourage investors to invest in the transm...

This chapter presents three MS Excel programs, namely, EMOO (Excel based Multi-Objective Optimization), NDS (Non-Dominated Sorting) and PM (Performance Metrics) useful for Multi-Objective Optimization (MOO) studies. The EMOO program is for finding non-dominated solutions of a given MOO problem. It has both binary-coded and realcoded NSGA-II (Elitist Non-Dominated Sorting Genetic Algorithm), and...

multi-objective optimization is the simultaneous consideration of two or more objective functions that are completely or partially inconflict with each other. the optimality of such optimizations is largely defined through the pareto optimality. multiple objective integer linear programs (moilp) are special cases of multiple criteria decision making problems. numerous algorithms have been desig...

Non-dominated sorting, dividing the population into several non-domination levels, is a basic step for many Pareto-based evolutionary multiobjective optimization (EMO) algorithms. Different from the generational scheme, where the selection of next parents is conducted after the generation of a population of offspring, the steady-state scheme updates the parent population whenever a new candidat...

Abstract: In order to solve the vehicle routing problem with pickup and delivery (VRPPD), this paper proposed an improved quantum genetic algorithm based on different constraint conditions. Firstly, a mathematical model was established aiming at minimizing the dispatching time and the total cost. Secondly, the paper proposes the improved quantum genetic algorithm and non dominated sorting strat...

The time–cost tradeoff problem is one of the most important and applicable problems in project scheduling area. There are many factors that force the mangers to crash the time. This factor could be early utilization, early commissioning and operation, improving the project cash flow, avoiding unfavorable weather conditions, compensating the delays, and so on. Since there is a need to allocate e...