Heuristics and metaheuristics are inevitable ingredients of most of the general purpose MIP solvers today, because of their contribution to the significant boost of the performance of exact methods. In the field of bi/multi-objective optimization, the interaction between the exact and metaheuristic communities is still fairly low. This article is one of the first steps towards reducing this gap...

Constrained optimization is a computationally difficult task, particularly if the constraint functions are non-linear and nonconvex. As a generic classical approach, the penalty function approach is a popular methodology which degrades the objective function value by adding a penalty proportional to the constraint violation. However, the penalty function approach has been criticized for its sen...

Heuristics and metaheuristics are inevitable ingredients of most of the general purpose ILP solvers today, because of their contribution to the significant boost of the performance of exact methods. In the field of bi/multi-objective optimization, to the best of our knowledge, it is still not very common to integrate ILP heuristics into exact solution frameworks. This paper aims to bring a stro...

Bi-objective problem; Hydrothermal scheduling; Economic dispatch; Emission dispatch; Combined economic emission dispatch Abstract The short-term combined economic emission hydrothermal scheduling is a bi-objective problem minimizing both fuel cost and emission of a hydrothermal system while satisfying thermal, hydro and system constraints. In this paper, an efficient cuckoo bird-inspired meta-h...

In this paper demonstrate MobiContext, a hybrid cloud-based Bi-Objective Recommendation Framework(BORF).The MobiContext utilizes multi-objective optimization techniques to create modified recommendations.To address the issues pertaining to cold start and datasparse,the BORF performs data preprocessing by using the Hub-Average(HA) inference method and the Weighted Sum Approachis implemented for ...

This paper is concerned with the bi-objective problem in searchbased software engineering for high-level decision-making. The paper presents bi-objective models for next release problem and modularization quality problem that characterized by the presence of two conflicting demands, for which the decision maker must find a suitable balance. The complex nature of such kind of problem has motivat...

in this paper, we present an application of intuitionistic fuzzyprogramming to a two person bi-matrix game (pair of payoffs matrices) for thesolution with mixed strategies using linear membership and non-membershipfunctions. we also introduce the intuitionistic fuzzy(if) goal for a choiceof a strategy in a payoff matrix in order to incorporate ambiguity of humanjudgements; a player wants to max...

This work studies the solution space topology of the Traveling Salesman Problem or TSP, as a bi-objective optimization problem. The concepts of category and range of a solution are introduced for the first time in this analysis. These concepts relate each solution of a population to a Pareto set, presenting a more rigorous theoretical framework than previous works studying global convexity for ...

The various meta-heuristic techniques for cloud and grid environment are: Ant Colony Optimization (ACO), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Tabu Search, Firefly Algorithm, BAT Algorithm and many more. So this paper represents the two types of meta-heuristic techniques, i.e. BAT algorithm and Genetic Algorithm. The different types of methods which comprise meta-heuristic ...

This paper studies charging scheduling problem of electric vehicles (EVs) in the scale of a microgrid (e.g., a university or town) where a set of charging stations are controlled by a central aggregator. A bi-objective optimization problem is formulated to jointly optimize total charging cost and user convenience. Then, a close-to-optimal online scheduling algorithm is proposed as solution. The...