Time-Cost Tradeoff and Resource-Scheduling Problems in Construction: A State-of-the-Art Review

Duration, cost, and resources are defined as constraints in projects. Consequently, Construction manager needs to balance between theses constraints to ensure that project objectives are met. Choosing the best alternative of each activity is one of the most significant problems in construction management to minimize project duration, project cost and also satisfies resources constraints as well as smoothing resources. Advanced computer technologies could empower construction engineers and project managers to make right, fast and applicable decisions based on accurate data that can be studied, optimized, and quantified with great accuracy. This article strives to find the recent improvements of resource-scheduling problems and time-cost trade off and the interacting between them which can be used in innovating new approaches in construction management. To achieve this goal, a state-of-the-art review, is conducted as a literature sample including articles implying three areas of research; time-cost trade off, constrained resources and unconstrained resources. A content analysis is made to clarify contributions and gaps of knowledge to help suggesting and specifying opportunities for future research

Optimal Biocompatible Solvent Design by Mixed-integer Hybrid Differential Evolution

In this study, a flexible optimization approach is introduced to design an optimal biocompatible solvent for an extractive fermentation process with cell-recycling. The optimal process/solvent design problem is formulated as a mixed-integer nonlinear programming model in which performance requirements of the compounds are reflected in the objectives and the constraints. A flexible or fuzzy optimization approach is applied to soften the rigid requirement for maximization of the production rate, extraction efficiency and to consider the solvent utilization rate as the softened inequality constraint to the process/solvent design problem. Such a trade-off problem is then converted to the goal attainment problem, which is described as the constrained mixed-integer nonlinear programming (MINLP) problem. Mixed-integer hybrid differential evolution with multiplier updating method is introduced to solve the constrained MINLP problem. The adaptive penalty updating scheme is more efficient to achieve a global design

Meta-heuristic algorithms in car engine design: a literature survey

Meta-heuristic algorithms are often inspired by natural phenomena, including the evolution of species in Darwinian natural selection theory, ant behaviors in biology, flock behaviors of some birds, and annealing in metallurgy. Due to their great potential in solving difficult optimization problems, meta-heuristic algorithms have found their way into automobile engine design. There are different optimization problems arising in different areas of car engine management including calibration, control system, fault diagnosis, and modeling. In this paper we review the state-of-the-art applications of different meta-heuristic algorithms in engine management systems. The review covers a wide range of research, including the application of meta-heuristic algorithms in engine calibration, optimizing engine control systems, engine fault diagnosis, and optimizing different parts of engines and modeling. The meta-heuristic algorithms reviewed in this paper include evolutionary algorithms, evolution strategy, evolutionary programming, genetic programming, differential evolution, estimation of distribution algorithm, ant colony optimization, particle swarm optimization, memetic algorithms, and artificial immune system