Multi-objective ant colony optimisation: A meta-heuristic approach to supply chain design

Moncayo–Martínez, Luis A.; Zhang, Zhengwen

doi:10.1016/j.ijpe.2010.11.026

Cited by 106 publications

(49 citation statements)

References 34 publications

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“…Thus, the weighted sum criteria has been adopted (Moncayo-Martinez & Zhang, 2011) to convert the multi-objective problem into a single-objective one assigning a weight (w) to each target function. Therefore the overall objective function is formulated as:…”

Section: Machine Loading Problem: Mathematical Formulationmentioning

confidence: 99%

Solving machine loading problem of flexible manufacturing systems using a modified discrete firefly algorithm

Bottani¹,

Centobelli²,

Cerchione³

et al. 2017

10.5267/j.ijiec

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This paper proposes a modified discrete firefly algorithm (DFA) applied to the machine loading problem of the flexible manufacturing systems (FMSs) starting from the mathematical formulation adopted by Swarnkar & Tiwari (2004). The aim of the problem is to identify the optimal jobs sequence that simultaneously maximizes the throughput and minimizes the system unbalance according to given technological constraints (e.g. available tool slots and machining time). The results of the algorithm proposed have been compared with the existing and most recent swarm-based approaches available in the open literature using as benchmark the set of ten problems proposed by Mukhopadhyay et al. (1992). The algorithm shows results that are comparable and sometimes even better than most of the other approaches considering both the quality of the results provided and the computational times obtained.

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Section: Machine Loading Problem: Mathematical Formulationmentioning

confidence: 99%

Solving machine loading problem of flexible manufacturing systems using a modified discrete firefly algorithm

Bottani¹,

Centobelli²,

Cerchione³

et al. 2017

10.5267/j.ijiec

View full text Add to dashboard Cite

show abstract

“…Yeh [21] proposed a Memetic Algorithm (MA), which is a combination of GA, greedy heuristic, and local search methods, for the same problem. Moncayo-Martinez and Zhang [22] proposed an algorithm based on Pareto Ant Colony Optimization as an e ective meta-heuristic method to solve multi-objective supply chain design problems. As an advantage, although the heuristic techniques do not necessarily nd the optimum solutions, they can produce a near-optimum solution with a rational computation time.…”

Section: Literature Reviewmentioning

confidence: 99%

Sustainable supply chain design with water environmental impacts and justice-oriented employment considerations: A case study in textile industry

2017

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Abstract. The concept of sustainability in supply chain management refers to a logical balance between economic development, environmental considerations, and social responsibilities. In this paper, a sustainable model has been proposed to design a supply chain network in textile industries considering the key environmental and social factors. Regarding the type of industry and characteristics of the area under study (Zanjan, northwest Iran), minimizing the negative e ects of wasteful extraction of ground waters and the environmental pollution resulting from industrial wastewaters and maximizing justicebased employment were considered. The supply chain consists of the following elements: suppliers, plants, distribution centers, water re nery centers, and customer zones. One of the important features of the proposed model is that it considers the lost opportunity cost of facilities and focuses on wastewater recycling in water re neries. To solve the model, the Multi-Objective Vibration Damping Optimization (MOVDO) algorithm has been used. In addition, to evaluate the proposed model, as a case study, the supply chain network design problem was solved in textile industry. In addition, to evaluate the solution performance of the used algorithm in comparison with that of the NSGA-II algorithm, ten random problems with di erent sizes were solved, and the results were analyzed using di erent indexes. All in all, the results show that the proposed method has the necessary performance.

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“…cost and time. Moncayo-Martínez and Zhang (2011) designed supply chain for a family of product comprising complex hierarchies of subassemblies and components. The supply chain design problem is to minimize the total supply chain cost when keep the total lead-times within required delivery due dates.…”

Section: Ant Colony Optimization (Aco)mentioning

confidence: 99%

Multi-objective optimization for supply chain management problem: A literature review

Trisna¹,

Marimin²,

Arkeman³

et al. 2016

10.5267/j.dsl

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Multi-objective optimization is an optimization problem with some conflicting objectives to be attained, simultanously. This paper reviewed literature about multi-objective optimization problems for supply chain management. The review aimed to provide the lastest research views and recomendations for further studies. We discussed the lastest ten years publications about multi-objective optimization for supply chain management. The scope of this review was classified into five categories i.e. problem statements, multi-objective frameworks, mathematical formulation modeling, optimization techniques, and representation of supply chain. Multi-objective optimization approaches, both classical and metaheuristic approaches, were discussed, accordingly. In this review, we conducted conclusion and recomendations about likelihood research directions in future.Science Ltd. All rights reserved. Growing 6 © 201

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Multi-objective ant colony optimisation: A meta-heuristic approach to supply chain design

Cited by 106 publications

References 34 publications

Solving machine loading problem of flexible manufacturing systems using a modified discrete firefly algorithm

Solving machine loading problem of flexible manufacturing systems using a modified discrete firefly algorithm

Sustainable supply chain design with water environmental impacts and justice-oriented employment considerations: A case study in textile industry

Multi-objective optimization for supply chain management problem: A literature review

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