Individuals encounter problems daily wherein varying numbers of constraints require delimitation of memory to target goal-satisfying information. Multiply-constrained problems, such as the compound remote associates, are commonly used to study this t...
The degree-constrained Steiner problem in graphs is well known in the literature. In an undirected graph, positive integer degree bounds are associated with nodes and positive costs with the edges. The goal is to find the minimum cost tree spanning a...
The optimal power flow problem is one of the most widely used problems in power system optimizations, which are multi-modal, non-linear, and constrained optimization problems. Effective constrained optimization methods can be considered in tackling t...
We consider the constrained ordered weighted averaging (OWA) aggregation problem with a single constraint and lower bounded variables. For the three-dimensional constrained OWA aggregation problem with lower bounded variables, we present four types o...
This article presents the resource-constrained project scheduling problem with the discounted cash flow maximization criterion from the perspective of a contractor. Cash flows are considered as the contractor’s expenses related to the execution...
In many fields of science and engineering, partial differential equation (PDE) constrained optimal control problems are widely used. We mainly solve the optimization problem constrained by the time-periodic eddy current equation in this paper. We pro...
A single constrained ordered weighted averaging aggregation (COWA) problem is of considerable importance in many disciplines. Two models are considered: the maximization COWA problem with lower bounded variables and the minimization COWA problem with...
We consider a decision-making problem to evaluate absolute ratings of alternatives from the results of their pairwise comparisons according to two criteria, subject to constraints on the ratings. We formulate the problem as a bi-objective optimizatio...
The dual-resource constrained flexible job shop scheduling problem with variable sublots (DRCFJSP-VS) can be decomposed into four subproblems: the sublot splitting subproblem, the sublot sequencing subproblem, the machine assignment subproblem, and t...
Recently, different metaheuristic techniques, their variants, and hybrid forms have been extensively used to solve economic load dispatch (ELD) problems with and without valve point loading (VPL) effects. Due to the randomization involved in these me...
This paper aims to present efficient alternative mixed-integer non-linear programming models and a customized hybrid metaheuristic, the Genetic-Based Algorithm (GBA), for a resource-constrained project-scheduling problem with a flexible network struc...
In this study, a low-carbon freight routing problem for time-sensitive goods is investigated in the context of water–rail–road multimodal transportation. To enhance the on-time transportation of time-sensitive goods, hard time windows are...
Aircraft maintenance scheduling is a critical task in air transportation and national defense security, characterized by complex multi-step procedures, strict precedence dependencies, and multi-resource constraints involving personnel skills and equi...
This paper deals with p-maxian problem on cycles with an upper bound on the distances of all facilities. We consider the case of
This paper proposes a multi-strategy improved pied kingfisher optimizer (MSIPKO), a novel metaheuristic algorithm designed to address constrained optimization problems (COPs). COPs are widely encountered in engineering and industrial applications and...
Firefly-Algorithm (FA) is an eminent nature-inspired swarm-based technique for solving numerous real world global optimization problems. This paper presents an overview of the constraint handling techniques. It also includes a hybrid algorithm, namel...
In this paper, we analyze an optimal control problem with a mixed cost function, which combines a terminal cost at the final state and an integral term involving the state and control variables. The problem includes both state and control constraints...
This paper proposes a multitasking-based genetic algorithm (MTGA-CMMO) to solve constrained multimodal multi-objective optimization problems (CMMOPs). In MTGA-CMMO, the main task is assisted by two auxiliary tasks to obtain all the feasible Pareto so...
This study compares two efficient formulations to solve corrective as well as preventive security-constrained (SC) DC-based optimal power flow (OPF) problems using linear sensitivity factors without sacrificing optimality. Both SCOPF problems are mod...
In this paper, we propose two novel inertial forward–backward splitting methods for solving the constrained convex minimization of the sum of two convex functions,
Constrained ordered weighted averaging (OWA) aggregation attempts to solve the OWA optimization problem subject to multiple constraints. The problem is nonlinear in nature due to the reordered variables of arguments in the objective function, and the...
The purpose of the research is the study of a nonconstant gradient constrained problem for nonlinear monotone operators. In particular, we study a stationary variational inequality, defined by a strongly monotone operator, in a convex set of gradient...
Construction projects are planned in a complex and dynamic environment characterized by high risks and uncertainties amidst resource constraints. Assessing construction schedule risk facilitates informed decision-making, especially in a resource-cons...
In this paper, a new approach to solve Chance Constrained Problems (CCPs) using huge data sets is proposed. Specifically, instead of the conventional mathematical model, a huge data set is used to formulate CCP. This is because such a large data set...
According to the characteristics of flexible job shop scheduling problems, a dual-resource constrained flexible job shop scheduling problem (DRCFJSP) model with machine and worker constraints is constructed such that the makespan and total delay are...
The k-means problem has been paid much attention for many applications. In this paper, we define the uncertain constrained k-means problem and propose a
This paper addresses the Distance-Constrained Inventory Routing Problem (DCIRP), a complex problem that combines inventory management and vehicle routing in a logistics context. The problem arises in the context of a specialty gas delivery company th...
In this paper, we study a variational problem with nonconstant gradient constraints. Several aspects related to problems with gradient constraints have been studied in the literature and have seen new developments in recent years. In the case of cons...
Iterative methods for solving constraint nonlinear monotone equations have been developed and improved by many researchers. The aim of this research is to present a modified three-term conjugate descent (TTCD) derivative-free method for constrained n...
Object detection models are usually trained and evaluated on highly complicated, challenging academic datasets, which results in deep networks requiring lots of computations. However, a lot of operational use-cases consist of more constrained situati...
This paper proposes an Enhanced Projection-Iterative-Methods-based Optimizer (EPIMO) to overcome the limitations of its predecessor, the Projection-Iterative-Methods-based Optimizer (PIMO), including deterministic parameter decay, insufficient divers...
With the increasing complexity of optimization problems, existing methods are often inadequate for addressing these challenges, creating a pressing need for more versatile and robust approaches capable of solving a wide range of optimization problems...
In this paper, first, we extend the analytical expression of the optimal solution of the constrained OWA aggregation problem with two comonotone constraints by also including the case when the OWA weights are arbitrary non-negative numbers. Then, we...
Studying the faster and more efficient method of solving the uncertain security-constrained unit commitment (SCUC) problem is an urgent need for the development of power systems under the background of large-scale wind power access and power dispatch...
This paper considers the constrained inverse problem based on the nonlinear convection-diffusion equation in the multiphase porous media flow. To solve this problem, a widely convergent homotopy method is introduced and proposed. To evaluate the perf...
The Competitive Swarm Optimizer (CSO) has emerged as a prominent technique for solving intricate optimization problems by updating only half of the population in each iteration. Despite its effectiveness, the CSO algorithm often exhibits a slow conve...
In this study, the multi-mode resource-constrained multi-project scheduling problems (MMRCMPSPs) considering supply management and sustainable approach in the construction industry under uncertain conditions have been investigated using evidence theo...
In the paper, we consider a generalization of the classical assignment problem, which is called the constrained assignment problem with bounds and penalties (CA-BP). Specifically, given a set of machines and a set of independent jobs, each machine ha...
The minimum-cost arborescence problem is a well-studied problem. Polynomial-time algorithms for solving it exist. Recently, a new variation of the problem called the Precedence-Constrained Minimum-Cost Arborescence Problem with Waiting Times was pres...
By considering the new forms of the notions of lower semicontinuity, pseudomonotonicity, hemicontinuity and monotonicity of the considered scalar multiple integral functional, in this paper we study the well-posedness of a new class of variational pr...
Diffusion models have shown strong promise for neural combinatorial optimization, yet existing approaches define the forward noising process over a fully connected graph, discarding the sparse topological structure inherent to the Traveling Salesman...
Resource-constrained project scheduling (RCPS) aims to minimize project duration under limited resource availabilities. The heuristic methods that are often used to solve the RCPS problem make use of different priority rules. The comparative merits o...
Proposing new strategies to improve the optimization performance of differential evolution (DE) is an important research study. The jSO algorithm was the announced winner of the Congress on Evolutionary Computation (CEC) 2017 competition on numerical...
10 January 2020
In order to solve the optimization problem of wet waste collection and transportation in Chinese cities, this paper constructs a chance-constrained low-carbon vehicle routing problem (CCLCVRP) model in waste management system and applies certain algo...
When solving complex constrained problems, how to efficiently utilize promising infeasible solutions is an essential issue because these promising infeasible solutions can significantly improve the diversity of algorithms. However, most existing cons...
This paper studies a parameter estimation problem for the non-linear diffusion equation within multiphase porous media flow, which has important applications in the field of oil reservoir simulation. First, the given problem is transformed into an op...
In industries such as aircraft or train manufacturing, large-scale manufacturing companies often manage several complex projects. Each of these projects includes multiple tasks that share a set of limited resources. Typically, these tasks are also su...
Multi-skilled resources have brought more flexibility to resource scheduling and have been a key factor in the research of resource-constrained project scheduling problems. However, existing studies are mainly limited to deterministic problems and ne...
This study addresses the dual resource constrained flexible job shop scheduling problem (DRCFJSP) with a multilevel product structure. The DRCFJSP is a strong NP-hard problem, and an efficient algorithm is essential for DRCFJSP. In this study, we pro...
Given several nonnegative matrices with a single pattern of allocation among their zero/nonzero elements, the average matrix should have the same pattern as well. This is the first tenet of the pattern-multiplicative average (PMA) concept, while the...
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