Discrete facility location and routing of obnoxious activities

Cappanera, Paola; Gallo, Giorgio; Maffioli, Francesco

doi:10.1016/s0166-218x(03)00431-1

Cited by 107 publications

(60 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several optimisation techniques have been applied in designing distribution systems. Optimisation techniques are used for reducing operational and overall costs in different distribution systems, for example, food and drink distribution (Watson-Gandy and Dohrn 1973), goods distribution (Perl andDaskin 1984, 1985), agricultural goods transport (Ljungberg et al 2007), forest harvesting (Rönnqvist et al 2007), waste collection (Apaydin and Gonullu 2008;Caballero et al 2007;Kulcar 1996), disposal of hazardous material (Alumur and Kara 2007), obnoxious facility location-routing (Cappanera et al 2004), small package shippers (Stenger et al 2012), shipping industry (Gunnarsson et al 2006), blood bank location (Or and Pierskalla 1979) and medical evacuation ( Chan et al 2001).…”

Section: Distribution Systems and The Food Supply Chainmentioning

confidence: 99%

A case analysis of a sustainable food supply chain distribution system—A multi-objective approach

Validi

Bhattacharya

Byrne

2014

International Journal of Production Economics

221

107

View full text Add to dashboard Cite

Abstract:Sustainable supply chain management is a topical area which is continuing to grow and evolve. Within supply chains, downstream distribution from producers to customers plays a significant role in the environmental performance of production supply chains. With consumer consciousness growing in the area of sustainable food supply, food distribution needs to embrace and adapt to improve its environmental performance, while still remaining economically competitive. With a particular focus on the dairy industry, a robust solution approach is presented for the design of a capacitated distribution network for a two-layer supply chain involved in the distribution of milk in Ireland. In particular the green multiobjective optimisation model minimises CO2 emissions from transportation and total costs in the distribution chain. These distribution channels are analysed to ensure the non-dominated solutions are distributed along the Pareto fronts. A multi-attribute decision-making approach, TOPSIS, has been used to rank the realistic feasible transportation routes resulting from the trade-offs between total costs and CO 2 emissions. The refined realistic solution space allows the decision-makers to geographically locate the sustainable transportation routes. In addition to geographical mapping the decision maker is also presented with a number of alternative analysed scenarios which forcibly open closed distribution routes to build resiliency into the solution approach. In terms of model performance, three separate GA based optimisers have been evaluated and reported upon. In the case presented NSGA-II was found to outperform its counterparts of MOGA-II and HYBRID.

show abstract

Section: Distribution Systems and The Food Supply Chainmentioning

confidence: 99%

A case analysis of a sustainable food supply chain distribution system—A multi-objective approach

Validi

Bhattacharya

Byrne

2014

International Journal of Production Economics

221

107

View full text Add to dashboard Cite

show abstract

“…These solution methods may be categorized as exact, heuristic, and metaheuristic approaches. For instance, (Cappanera, Gallo et al 2003) presented an obnoxious facility location-routing (OFLR) problem in which lagrangean relaxation (LR) was used to decompose the problem into two subproblems of location and routing and two lagrangean heuristics were presented.…”

Section: Literature Reviewmentioning

confidence: 99%

Capacitated location-routing problem with time windows under uncertainty

Zarandi

Hemmati

Davari

et al. 2013

Knowledge-Based Systems

View full text Add to dashboard Cite

This paper puts forward a location-routing problem with time windows (LRPTW) under uncertainty. It has been assumed that demands of customers and travel times are fuzzy variables. A fuzzy chance constrained programming (CCP) model has been designed using credibility theory and a simulation-embedded simulated annealing (SA) algorithm is presented in order to solve the problem. To initialize solutions of SA, a heuristic method based on fuzzy c-means (FCM) clustering with Mahalanobis distance and sweep method has been employed. The numerical experiments which were carried out, clearly attest that the proposed solution approach is both effective and robust in solving problems with up to 100 demand nodes in reasonable times.

show abstract

“…The multiple knapsack problem was first developed by Eilon and Christofides (1971) as a cargo loading problem, and can be solved using algorithms presented by Martello and Toth (1981) and Pisinger (1999) . Second, in addition to the weight constraints, it includes demand constraints, as used by Cappanera (1999) , whose model also includes multiple dimensions of item cost; in the Marine squad problem, only weight is used. Algorithms for solving multidimensional knapsack problems with demand constraints are given by Arntzen, Hvattum, and Lokketangen (2006), Cappanera and Trubian (2005) , and Hvattum and Lokketangen (2007) .…”

Section: Introductionmentioning

confidence: 99%

“…Algorithms for solving multidimensional knapsack problems with demand constraints are given by Arntzen, Hvattum, and Lokketangen (2006), Cappanera and Trubian (2005) , and Hvattum and Lokketangen (2007) . They have been used in capital budgeting by Beaujon, Marin, and McDonald (2001) , and in location problems by Cappanera (1999) and Plastria (2001) . Third, some of the items under consideration can be transferred between Marines, and others (primarily clothing items) cannot.…”

Section: Introductionmentioning

confidence: 99%

An application of the multiple knapsack problem: The self-sufficient marine

Simon

Apte

Regnier

2017

European Journal of Operational Research

View full text Add to dashboard Cite

a b s t r a c tSelf-Sufficiency (SS) is the ability to maintain capability without external support or aid. Operations in austere environments with limited functional infrastructure and logistical support, which are common in humanitarian assistance and disaster relief as well as military operations, must be self-sufficient. In this paper, we explore the challenges of SS in the United States Marine Corps (USMC). Marines engage in a wide variety of expeditionary operations, and must function without logistical support for long stretches of time. They face competing constraints, including the load that a squad can carry, mission requirements, resources required for sustainment, and the extent to which resources can be shared. We extend the knapsack problem in several ways to model a Marine squad's decisions regarding what items to carry and how to distribute them. The Office of Naval Research found the models and the results to be significant as baseline analysis for the resource demands of a self-sufficient squad. Though the data and scenarios are USMC-specific, the challenges of SS can be found in any expeditionary undertakings or operations in austere environments.

show abstract

Discrete facility location and routing of obnoxious activities

Cited by 107 publications

References 12 publications

A case analysis of a sustainable food supply chain distribution system—A multi-objective approach

A case analysis of a sustainable food supply chain distribution system—A multi-objective approach

Capacitated location-routing problem with time windows under uncertainty

An application of the multiple knapsack problem: The self-sufficient marine

Contact Info

Product

Resources

About