Decomposition-based algorithms for multi-objective optimization problems have increased in popularity in the past decade. Although their convergence to the Pareto optimal front (PF) is in several instances superior to that of Pareto-based algorithms, the problem of selecting a way to distribute or guide these solutions in a high-dimensional space has not been explored. In this work, we introduc...

In this paper, redundancy allocation problem for system reliability has been presented with entropy as objective function. This model using entropy has been used to account for the lack of expert’s information. The goal of entropy redundancy allocation problem is to find out optimal level of redundancies at each subsystem in a way that maximizes reliability and entropy of the system subject to ...

In this paper, a modified invasive weed optimization (IWO) algorithm is presented for optimization of multiobjective flexible job shop scheduling problems (FJSSPs) with the criteria to minimize the maximum completion time (makespan), the total workload of machines and the workload of the critical machine. IWO is a bio-inspired metaheuristic that mimics the ecological behaviour of weeds in colon...

This paper proposes a maximum-entropy based multi-objective genetic algorithm approach for the design optimization of water distribution networks. The novelty is that in contrast to previous research involving statistical entropy the algorithm can handle multiple operating conditions. We used NSGA II and EPANET 2 and wrote a subroutine that calculates the entropy value for any given water distr...

This work presents PESMOC, Predictive Entropy Search for Multi-objective Bayesian Optimization with Constraints, an information-based strategy for the simultaneous optimization of multiple expensive-to-evaluate black-box functions under the presence of several constraints. PESMOC can hence be used to solve a wide range of optimization problems. Iteratively, PESMOC chooses an input location on w...

We present PESMO, a Bayesian method for identifying the Pareto set of multi-objective optimization problems, when the functions are expensive to evaluate. The central idea of PESMO is to choose evaluation points so as to maximally reduce the entropy of the posterior distribution over the Pareto set. Critically, the PESMO multi-objective acquisition function can be decomposed as a sum of objecti...

Alligator weed Alternanthera philoxeroides (Mart.) Griseb (Amaranthaceae) is being reported for the first time from Kashmir, India. Alternanthera philoxeroides was collected in 2008 during the vegetation survey of Wular Lake, a wetland of international importance under Ramsar convention. Alternanthera philoxeroides is a noxious invasive weed widespread throughout the world. We suggested that al...

In software industry, a common problem that the companies face is to decide what requirements should be implemented in the next release of the software. This paper aims to address the multi-objective next release problem using search based methods such as multi-objective evolutionary algorithms for empirical studies. In order to achieve the above goal, a requirement-dependency-based multi-objec...

In this paper, the performances of the Artificial Bee Colony (ABC) Algorithm and Invasive Weed Optimization (IWO) Algorithm are compared on the basis of modified versions of five well known benchmark functions. The modifications are performed on these functions in order to get rid of the symmetrical properties of the selected functions. Further a solution space is shifted so that the optimal fu...