A multicriteria facility location model for municipal solid waste management in North Greece

Up to 2002, Hellenic Solid Waste Management (SWM) policy specified that each of the country’s 54 prefectural governments plan its own SWM system. After 2002, this authority was shifted to the country’s 13 regions entirely. In this paper, we compare and contrast regional and prefectural SWM planning in Central Macedonia. To design the prefectural plan, we assume that each prefecture must be self-sufficient, and we locate waste facilities in each prefecture. In contrast, in the regional plan, we assume cooperation between prefectures and locate waste facilities to serve the entire region. We present a new multicriteria mixed-integer linear programming model to solve the location–allocation problem for municipal SWM at the regional level. We apply the lexicographic minimax approach to obtain a “fair” nondominated solution, a solution with all normalized objectives as equal to one another as possible. A solution to the model consists of locations and technologies for transfer stations, material recovery facilities, incinerators and sanitary landfills, as well as the waste flow between these locations.     

A bi-objective model for the location of landfills for municipal solid waste

This paper models the locations of landfills and transfer stations and simultaneously determines the sizes of the landfills that are to be established. The model is formulated as a bi-objective mixed integer optimization problem, in which one objective is the usual cost-minimization, while the other minimizes pollution. As a matter of fact, pollution is dealt with a two-pronged approach: on the one hand, the model includes constraints that enforce legislated limits on pollution, while one of the objective functions attempts to minimize pollution effects, even though solutions may formally satisfy the letter of the law. The model is formulated and solved for the data of a region in Chile. Computational results for a variety of parameter choices are provided. These results are expected to aid decision makers in the choice of excluding and choosing sites for solid waste facilities.     

Global aspects of the continuous and discrete Newton method: A case study

Newton's method has recently become one of the paradigms in the revival of Julia set theory and complex dynamical systems. This paper, to a large extent experimental in nature, investigates Newton's method for some particular model problems as a real dynamical system of several simultaneous equations guided by the Julia set theory.     

A discrete long-term location–price problem under the assumption of discriminatory pricing: Formulations and parametric analysis

We consider a competitive location problem in which a new firm has to make decisions on the locations of several new facilities as well as on its price setting in order to maximise profit. Under the assumption of discriminatory prices, competing firms set a specific price for each market area. The customers buy one unit of a single homogeneous price-inelastic product from the facility that offers the lowest price in the area the consumers belong to. Three customer choice rules are considered in order to break ties in the offered prices. We prove that, considering long-term competition on price, this problem can be reduced to a problem with decisions on location only. For each one of the choice rules the location problem is formulated as an integer programming model and a parametric analysis of these models is given. To conclude, an application with real data is presented.     

A bibliography for some fundamental problem categories in discrete location science

Following a brief taxonomy of the broad field of facility location modeling, this paper provides an annotated bibliography of recent papers in two branches of discrete location theory and modeling. In particular, we review papers related to (1) the median and plant location models and (2) to center and covering models. We show how the contributions of the papers we review are embedded in the field. A summary and outlook conclude the paper.     

Combination of MCDM and covering techniques in a hierarchical model for facility location: A case study

In this paper, locating some warehouses as distribution centers (DCs) in a real-world military logistics system will be investigated. There are two objectives: finding the least number of DCs and locating them in the best possible locations. The first objective implies the minimum cost of locating the facilities and the latter expresses the quality of the DCs locations, which is evaluated by studying the value of appropriate attributes affecting the quality of a location. Quality of a location depends on a number of attributes; so the value of each location is determined by using Multi Attribute Decision Making models, by considering the feasible alternatives, the related attributes and their weights according to decision maker’s (DM) point of view. Then, regarding the obtained values and the minimum number of DCs, the two objective functions are formed. Constraints imposed on these two objectives cover all centers, which must be supported by the DCs. Using Multiple Objective Decision Making techniques, the locations of DCs are determined. In the final phase, we use a simple set partitioning model to assign each supported center to only one of the located DCs.     

Managing inventories with one-way substitution: A newsvendor analysis

This paper presents an insightful approach to analyze two-item periodic inventory systems with one-way substitution. The objective is to minimize the expected total cost per period, which consists of expected purchasing costs, expected inventory holding costs, expected shortage costs, and expected adjustment costs. This approach helps derive the optimality conditions in both single-period and infinite horizon settings and yields useful insights into the impact of substitution on the service level, the optimality of a borderline case in which the order-up-to level of the inflexible item is reduced to zero, and the pivotal role of the purchasing cost.     

Faithfulness in chain graphs: The discrete case

This paper deals with chain graphs under the classic Lauritzen–Wermuth–Frydenberg interpretation. We prove that the strictly positive discrete probability distributions with the prescribed sample space that factorize according to a chain graph G with dimension d have positive Lebesgue measure wrt , whereas those that factorize according to G but are not faithful to it have zero Lebesgue measure wrt . This means that, in the measure-theoretic sense described, almost all the strictly positive discrete probability distributions with the prescribed sample space that factorize according to G are faithful to it.     

A discrete bilevel brain storm algorithm for solving a sales territory design problem: a case study

A sales territory design problem faced by a manufacturing company that supplies products to a group of customers located in a service region is addressed in this paper. The planning process of designing the territories has the objective to minimizing the total dispersion of the customers without exceeding a limited budget assigned to each territory. Once territories have been determined, a salesperson has to define the day-by-day routes to satisfy the demand of customers. Currently, the company has established a service level policy that aims to minimize total waiting times during the distribution process. Also, each territory is served by a single salesperson. A novel discrete bilevel optimization model for the sales territory design problem is proposed. This problem can be seen as a bilevel problem with a single leader and multiple independent followers, in which the leader’s problem corresponds to the design of territories (manager of the company), and the routing decision for each territory corresponds to each follower. The hierarchical nature of the current company’s decision-making process triggers some particular characteristics of the bilevel model. A brain storm algorithm that exploits these characteristics is proposed to solve the discrete bilevel problem. The main features of the proposed algorithm are that the workload is used to verify the feasibility and to cluster the leader’s solutions. In addition, four discrete mechanisms are used to generate new solutions, and an elite set of solutions is considered to reduce computational cost. This algorithm is used to solve a real case study, and the results are compared against the current solution given by the company. Results show a reduction of more than 20% in the current costs with the solution obtained by the proposed algorithm. Furthermore, a sensitivity analysis is performed, providing interesting managerial insights to improve the current operations of the company.     

A methodology for sensitivity analysis in three-criteria problems: A case study in municipal management

This paper describes part of an on-going research project studying the issues of the application of Multicriteria Decision Aid Methodologies in real case-studies at the local level of the Portuguese Public Administration.In a first part, it address the complexity of decision situations in municipal management in general and the significance of decision analysis, namely multicriteria evaluation procedures, in conducting decision aid processes in that environment (Section 1).In a second part, a case study is described (Section 2), followed by its discussion in the ‘space of the weights’ in the context of different particular types of possible problem formulations (Section 3). For this purpose, an extension of Triangular Decision Technique is first proposed, followed by the presentation of a new Outranking approach, designated by ‘Outweigh’ analysis, which will permit the enrichment of the discussion.     

Mathematical analysis of memristor through fractal-fractional differential operators: A numerical study

The newly generalized energy storage component, namely, memristor, which is a fundamental circuit element so called universal charge-controlled mem-element, is proposed for controlling the analysis and coexisting attractors. The governing differential equations of memristor are highly nonlinear for mathematical relationships. The mathematical model of memristor is established in terms of newly defined fractal-fractional differential operators so called Atangana-Baleanu, Caputo-Fabrizio, and Caputo fractal-fractional differential operator. A novel numerical approach is developed for the governing differential equations of memristor on the basis of Atangana-Baleanu, Caputo-Fabrizio, and Caputo fractal-fractional differential operator. We discussed chaotic behavior of memristor under three criteria such as (i) varying fractal order, we fixed fractional order; (ii) varying fractional order, we fixed fractal order; and (ii) varying fractal and fractional orders simultaneously. Our investigated graphical illustrations and simulated results via MATLAB for the chaotic behaviors of memristor suggest that newly presented Atangana-Baleanu, Caputo-Fabrizio, and Caputo fractal-fractional differential operators generate significant results as compared with classical approach.     

Optimization with simulation and multiobjective analysis in industrial decision-making: A case study

In order to ensure that end of life vehicles (ELVs) are discarded without endangering the environment, appropriate collection systems should be set up. In accordance with the European Community Directive, the construction of an industrial plant for the decontamination and recycling processes of ELVs is currently being planned in Navarra (Spain). The aim of this study is to optimize the design and management of this industrial plant. We will provide a modelling framework that integrates different OR methodologies: queueing networks, optimization with simulation, evolutionary computation and multiobjective methods.     

Parsimonious representation of nonlinear dynamical systems through manifold learning: A chemotaxis case study

Nonlinear manifold learning algorithms, such as diffusion maps, have been fruitfully applied in recent years to the analysis of large and complex data sets. However, such algorithms still encounter challenges when faced with real data. One such challenge is the existence of “repeated eigendirections,” which obscures the detection of the true dimensionality of the underlying manifold and arises when several embedding coordinates parametrize the same direction in the intrinsic geometry of the data set. We propose an algorithm, based on local linear regression, to automatically detect coordinates corresponding to repeated eigendirections. We construct a more parsimonious embedding using only the eigenvectors corresponding to unique eigendirections, and we show that this reduced diffusion maps embedding induces a metric which is equivalent to the standard diffusion distance. We first demonstrate the utility and flexibility of our approach on synthetic data sets. We then apply our algorithm to data collected from a stochastic model of cellular chemotaxis, where our approach for factoring out repeated eigendirections allows us to detect changes in dynamical behavior and the underlying intrinsic system dimensionality directly from data.     

A measure of mutual complete dependence in discrete variables through subcopula

Siburg and Stoimenov [12] gave a measure of mutual complete dependence of continuous variables which is different from Spearman's ρ and Kendall's τ. In this paper, a similar measure of mutual complete dependence is applied to discrete variables. Also two measures for functional relationships, which are not bijection, are investigated. For illustration of our main results, several examples are given.     

Obnoxious-facility location and data-envelopment analysis: A combined distance-based formulation

We have broadened the classic anti-center models to include generalized-distance measures. It includes in the inherent proximity measures other cost/benefit metrics. Unlike classic data envelopment analysis (DEA), the combined location/DEA model proposed here assumes disposability of input/output's only. It represents a more flexible formulation. The locations of multiple sites are analyzed using a binary integer program, while evaluation is performed by the full strength of a DEA model. Through a case study, we show how location and DEA models can be used together to more realistically characterize a siting decision.     

New results in Sridhar filtering theory: The discrete case

A nonlinear time-varying adaptive filter is introduced, and its derivation using optimal control concepts is given in detail. The filter, which is called the discrete Pontryagin filter, is basically an extension to Sridhar filtering theory. The proposed approach can easily replace the conventional methods of autoregressive (AR) and autoregressive moving average (ARMA) models in their many applications. Instead of using a large number of time-invariant parameters to describe the signal or the time series, a single time-varying function is enough. This function is estimated using optimization techniques. Many features are gained using this approach, such as simpler and compact filter equations and better overall accuracy. The statistical properties of the filter are given, and it is shown that the signal estimate will converge in thepth mean to the true value.     

Dynamic dairy facility location and supply chain planning under traffic congestion and demand uncertainty: A case study of Tehran

In this paper, dynamic dairy facility location and supply chain planning are studied through minimizing the costs of facility location, traffic congestion and transportation of raw/processed milk and dairy products under demand uncertainty. The proposed model dynamically incorporates possible changes in transportation network, facility investment costs, monetary value of time and changes in production process. In addition, the time variation and the demand uncertainty for dairy products in each period of the planning horizon is taken into account to determine the optimal facility location and the optimal production volumes. Computational results are presented for the model on a number of test problems. Also, an empirical case study is conducted in order to investigate the dynamic effects of traffic congestion and demand uncertainty on facility location design and total system costs.     

On the application of a transportation model for revenue optimization in waste management: a case study

This paper describes an interactive decision support system called Opti-Link which has been developed for a company operating in the area of waste and raw material management. Built around a specific transportation problem, the system is used to maximize the revenue generated by selling waste paper to paper mills. Furthermore, the dual variables of the linear program allow the planner to identify upper bounds for setting bid prices to buy waste paper from waste collection companies. First operational results indicate a significant increase in profit while at the same time the duration of the planning process could be cut by more than half.