Emergencies such as machine breakdowns and rush orders greatly affect the production activities of manufacturing enterprises. How to deal with rescheduling problem after emergencies have high practical value. Meanwhile, under background intelligent manufacturing, automatic guided vehicles are gradually emerging in To disturbances flexible job shop scheduling vehicle transportation, a mixed-inte...

The use of heuristic evolutionary algorithms to address the problem of portfolio optimisation has been well documented. In order to decide which assets to invest in and how much to invest, one needs to assess the potential risk and return of different portfolios. This problem is ideal for solving using a Multi-Objective Evolutionary Algorithm (MOEA) that maximises return and minimises risk. We ...

The 0/1 knapsack problem is a well-known problem, which appears in many real domains with practical importance. The problem is NP-complete. The multiobjective 0/1 knapsack problem is a generalization of the 0/1 knapsack problem in which multiple knapsacks are considered. Many algorithms have been proposed in the past five decades for both single and multiobjective knapsack problems. A new versi...

This paper considers supply chain design in green logistics. We formulate the choice of an environmentally conscious chain design as a multi-objective optimization (MOO) problem and approximate the Pareto front using the weighted sum and epsilon constraint scalarization methods as well as with two popular genetic algorithms, NSGA-II and SPEA2. We extend an existing case study of green supply ch...

Interpretability and accuracy are two important features of fuzzy systems which are conflicting in their nature. One can be improved at the cost of the other and this situation is identified as “Interpretability-Accuracy Trade-Off”. To deal with this trade-off Multi-Objective Evolutionary Algorithms (MOEA) are frequently applied in the design of fuzzy systems. Several novel MOEA have been propo...

The Bus Driver Rostering Problem (DRP) consists of assigning bus drivers to daily duties during a planning period. The problem considers hard constraints imposed by institutional and legal requirements. Solutions should as much as possible satisfy soft constraints that qualify rosters according to either the company’s or the drivers’ interests. A bi-objective version of the DRP is considered an...

Under mild conditions, the Pareto set of a continuous multi-objective optimization problem exhibits certain regularity. We have recently advocated taking into consideration such regularity in designing multi-objective evolutionary algorithms. Following our previous work on using Local Principal Component Analysis for capturing the regularity, this paper presents a new approach for acquiring and...

Abstract This paper explores the trade-off between redeveloping an urban site with higher density and maintaining solar access for surrounding context in hot dry climate of Tel Aviv. Such trade-offs are important future development Middle East, where densification is a demographic environmental need. We explore this multi-objective optimization (MOO). Specifically, we benchmark seven MOO algori...

Convergence and diversity are two performance requirements that should be paid attention to in evolutionary algorithms. Most multiobjective algorithms (MOEAs) try their best maintain a balance between the aspects, which poses challenge convergence of MOEAs early process. In this paper, many-objective optimization algorithm based on staged coordination selection, consists stages, is proposed sta...

Building envelope optimization always occupies an important place in sustainable building design. This paper selects a large-scale space as research object, which requires more complex and flexible fenestration system. On the premise of complying with some rules, the fenestration is easily managed by adjusting the number and position of small rectangular patches on the grid-based exposed surfac...