As one of the most challenging combinatorial optimization problems in scheduling, the resource-constrained project scheduling problem (RCPSP) has attracted numerous scholars’ interest resulting in considerable research in the past few decades. However, most of these papers focused on the single objective RCPSP; only a few papers concentrated on the multi-objective resource-constrained project s...

Many control problems involve simultaneous optimization of multiple performance measures that are often noncommensurable and competing with each other. Traditionally, classical optimization algorithms based on nonlinear programming or optimal control theory is applied to obtain the solution of such problems using different scalar approaches. The presence of multiple objectives in a problem usua...

Determining the contribution of an agent to a system-level objective function (credit assignment) is a key area of research in cooperative multiagent systems. Multi-objective optimization is a growing area of research, though mostly focused on single agent settings. Many real-world problems are multiagent and multi-objective, (e.g., air traffic management, scheduling observations across multipl...

This paper proposes a mathematical model as the bi-objective capacitated multi-vehicle allocation of customers to distribution centers. An evolutionary algorithm named non-dominated sorting ant colony optimization (NSACO) is used as the optimization tool for solving this problem. The proposed methodology is based on a new variant of ant colony optimization (ACO) specialized in multi-objective o...

this paper presents a multi-objective resource-constrained project scheduling problem with positive and negative cash flows. the net present value (npv) maximization and making span minimization are this study objectives. and since this problem is considered as complex optimization in np-hard context, we present a mathematical model for the given problem and solve three evolutionary algorithms;...

time-dependent vehicle routing problem is one of the most applicable but least-studied variants of routing and scheduling problems. in this paper, a novel mathematical formulation of time-dependent vehicle routing problems with heterogeneous fleet, hard time widows and multiple depots, is proposed. to deal with the traffic congestions, we also considered that the vehicles are not forced to come...

This paper presents a bi-objective MIP model for the flexible flow shop scheduling  problem (FFSP) in which the total weighted tardiness and the energy consumption are minimized simultaneously. In addition to considering unrelated machines at each stage, the set-up times are supposed to be sequence- and machine-dependent, and it is assumed that jobs have different release tim...

The gaining returns in line with risks is always a major concern for market play-ers. This study compared the selection of stock portfolios based on the strategy of buying and retaining winning stocks and the purchase strategy based on the level of investment risks. In this study, the two-step optimization algorithms NSGA-II and SPEA-II were used to optimize the stock portfolios. In order to de...

An improved harmony search algorithm for constrained multi-objective optimization problems is proposed in this paper. Inspired by Particle Swarm Optimization, an inductor particle is introduced to speed up the convergence rate of the CMOHS. Two populations are adopted to increase the opportunity of finding the optimal solutions. Numerical experiments are divided into two parts: the first one co...

An improved harmony search algorithm for constrained multi-objective optimization problems is proposed in this paper. Inspired by Particle Swarm Optimization, an inductor particle is introduced to speed up the convergence rate of the CMOHS. Two populations are adopted to increase the opportunity of finding the optimal solutions. Numerical experiments are divided into two parts: the first one co...