We have previously developed an adaptation of the simulated annealing for multi-objective combinatorial optimization (MOCO) problems to construct an approximation of the e$cient set of such problem. In order to deal with large-scale problems, we transform this approach to propose an interactive procedure. The method is tested on the multi-objective knapsack problem and the multi-objective assig...

This paper presents a multi-objective Particle Swarm Optimization (PSO) algorithm for worker assignment and mixed-model assembly line balancing problem when task times depend on the worker’s skill level. The objectives of this model are minimization of the number of stations (equivalent to the maximization of the weighted line efficiency), minimization of the weighted smoothness index and minim...

In this paper we are concerned with finding the Pareto optimal front or a good approximation to it. Since non-dominated solutions represent the goal in multiobjective optimisation, the dominance relation is frequently used to establish preference between solutions during the search. Recently, relaxed forms of the dominance relation have been proposed in the literature for improving the performa...

We combine concepts from numerous papers to provide a derivation and description of a generalized Probabilistic Multi-Hypothesis Tracker that can track multiple targets in a cluttered environment, utilizing multiple sensors and feature measurements, if available. Additionally, we provide a full derivation of the algorithm, including parts omitted or abbreviated in other work. We also provide an...

We proposed a passenger control strategy and train operation plan collaborative optimization (PCS&TOP) model to schedule the that improves efficiency of passengers’ travel reduces cost for rail transit network. The is an integer non linear programming aims minimize entrance platform waiting time passengers trains. timetable variable formation are integrated optimized, turnaround rolling sto...

In this paper, we present a new algorithm — an Enhanced Annealing Genetic Algorithm for Multi-Objective Optimization problems (MOPs). The algorithm tackles the MOPs by a new quantitative measurement of the Pareto front coverage quality — Coverage Quotient. We then correspondingly design an energy function, a fitness function and a hybridization framework, and manage to achieve both satisfactory...

this paper presents a multi-criteria vehicle routing problem with soft time windows (vrpstw) to mini-mize fleet cost, routes cost, and violation of soft time windows penalty. in this case, the fleet is heterogene-ous. the vrpstw consists of a number of constraints in which vehicles are allowed to serve customers out of the desirable time window by a penalty. it is assumed that this relaxation a...

In this paper, a hybrid evolutionary algorithm (HEA) is proposed to determine the optimal placement of multi-type flexible AC transmission system (FACTS) devices to simultaneously maximize the total transfer capability (TTC) and minimize the system real power loss of power transfers in deregulated power systems. Multi-objective optimal power flow (OPF) with FACTS devices including TTC, power lo...