In this work, we proposed a low‐complexity hybrid layered tabu‐likelihood ascent search (LTLAS) algorithm for large multiple‐input multiple‐output (MIMO) system. The conventional layered tabu search ...(LTS) approach involves many partial reactive tabu searches (RTSs), and each RTS requires an initialization and searching phase. In the proposed algorithm, we restricted the upper limit of the number of RTS operations. Once RTS operations exceed the limit, RTS will be replaced by low‐complexity likelihood ascent search (LAS) operations. The block‐based detection approach is considered to maintain a higher signal‐to‐noise ratio (SNR) detection performance. An efficient precomputation technique is derived, which can suppress redundant computations. The simulation results show that the bit error rate (BER) performance of the proposed detection method is close to the conventional LTS method. The complexity analysis shows that the proposed method has significantly lower computational complexity than conventional methods. Also, the proposed method can reduce almost 50% of real operations to achieve a BER of 10−3.
This paper develops an improved tabu search algorithm (ITS) for economic dispatch (ED) with noncontinuous and nonsmooth cost functions. ITS employs a flexible memory system to avoid the entrapment in ...a local minimum and developed the ideal of "distance" to the fitness to accelerate optimization. The new approach extends simple tabu search algorithm (STS) to real valued optimization problem and applies parallelism to weaken the dependence of the convergence rate of modified tabu search algorithm (NITS) on the initial condition. Effectiveness of the method was compared with many conventional methods. Results show that the proposed algorithm can provide accurate solutions with reasonable performance and has a great potential for other applications in the power system.
With the crash of climate change in India, due to global warming and other factors, preponderance of the agricultural crops are being deficiently exaggerated in terms of their recital over a period ...of last two decades. Envisaging the crop yield well ahead of its harvest would help the policymakers and farmers for taking appropriate measures for marketing and storage. Such predictions will also help to escalate the crops productions. This chapter presents various methods and techniques that are used today for predicting and modeling crop yields. The chapter also highlights the problems faced by the farmers of Thanjavur district due to climate change. The district is also called the rice bowl of Tamilnadu, located in the Cauvery delta region. In addition to this, this chapter also present a novel recommendation system that uses random forest for recommending suitable crops for the area under study and tabu search optimization for increasing crop production. The crops are recommended based on (a) soil properties, (b) crop characteristics, (c) climate parameters. The crops, namely maize, finger millet, rice, and onions, are considered for study. Depending on the prediction techniques, restorative crops are chosen for the corresponding climate conditions. The proposed system is integrated with location specific soil properties as real time input and recommends the suitable crop with good outcome considering the input and climate parameters.
In this letter, we propose a method to introduce tabu search into Edge Assembly Crossover (EAX), which is an effective crossover method in solving the traveling salesman problem (TSP) using genetic ...algorithms. The proposed method, called EAX-tabu, archives the edges that have been exchanged over the past few generations into the tabu list for each individual and excludes them from the candidate edges to be exchanged when generating offspring by the crossover, thereby increasing the diversity of edges in the offspring. The effectiveness of the proposed method is demonstrated through numerical experiments on medium-sized instances of TSPLIB and VLSI TSP.
The application of optimization techniques to home care service planning has received increasing attention, as more patients are in need of dedicated care. Currently, the problem of scheduling home ...care services is not performed in an optimal way taking into account the complexities of the problem in an integrated way and thus there is substantial room for improvement as the scale of the industry increases. We address the home care planning problem by formulating a mixed integer programming model that simultaneously considers the assignment of nurses to patients, the scheduling of nurses’ workdays and the routing of nurses between patients. The problem is formulated as a multi-objective problem that aims to minimize healthcare-associated service and routing costs while maximizing compatibility of nurses and patients. Two approaches are developed to solve the problem, namely a branch-and-price algorithm as well as a two-stage meta-heuristic. We evaluate the performance of each solution approach, and also assess the value of integrating the assignment, scheduling and routing decisions versus solving these problems sequentially. Computational studies demonstrate that our multi-objective model can bring about savings in healthcare costs and improve the compatibility between nurses and patients. These studies also demonstrate that solutions with increased compatibility do not necessarily come at a price of increased healthcare costs. Furthermore, we show that the two approaches we develop are superior to solving the mixed integer programming model using a conventional solver.
•We study a problem of routing and assignment arising from home healthcare delivery.•We build a mixed-integer program model and a branch-and-price algorithm.•We also develop a two-stage meta-heuristic based on Tabu search.•We run extensive computational experiments to test the algorithms.•We run experiments to analyze different models to gain policy insights.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Energy-efficient scheduling is highly necessary for energy-intensive industries, such as glass, mould or chemical production. Inspired by a real-world glass-ceramics production process, this paper ...investigates a bi-criteria energy-efficient two-stage hybrid flow shop scheduling problem, in which parallel machines with eligibility are at stage 1 and a batch machine is at stage 2. The performance measures considered are makespan and total energy consumption. Time-of-use (TOU) electricity prices and different states of machines (working, idle and turnoff) are integrated. To tackle this problem, a mixed integer programming (MIP) is formulated, based on which an augmented ε-constraint (AUGMECON) method is adopted to obtain the exact Pareto front. A problem-tailored constructive heuristic method with local search strategy, a bi-objective tabu search algorithm and a bi-objective ant colony optimisation algorithm are developed to deal with medium- and large-scale problems. Extensive computational experiments are conducted, and a real-world case is solved. The results show effectiveness of the proposed methods, in particular the bi-objective tabu search.
Full text
Available for:
BFBNIB, GIS, IJS, IZUM, KILJ, KISLJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
After being the subject of many studies up until 1914, totemism seemed to disappear from the literature. The publication of Freud’s work Totem and Taboo was initially greeted with silence, and ...subsequently with critical and hostile reactions. C. Lévi-Strauss was one of the few to devote a book to totemism but considered it as an illusion, although a number of prominent members of the English school of Social Anthropology contested this view, describing the direction adumbrated by Freud’s enquiry as “highly pertinent”.
Totemism appears in Freud’s work as a way of dealing with one of the canonical forms of human destructiveness, namely parricide. Why did eminent men find it impossible to utilise Freud’s book and those studies that followed it in the interwar period?
The mass murders in Nazi Germany and Stalinist Russia, however different they may have been, both generated a profound sense of horror that made their consequences largely unrepresentable for Europeans for more than thirty years. Did this delay, and the attitudes of the following generations towards authority, result from an unconscious logic of “resistance” aimed at re-establishing refusals that did not take place at the time? The Western world seems to have forgotten the strength of the mixed family ties of tribes, casts, and religions that are in fact at work in the psychic life of a great number of men and women in the world.
•We study a zone districting problem to regulate reliability of public census data.•The problem can address equity for poorly sampled population segments.•Problem is a variation of max-p-regions ...problem with margin of error bound.•A tabu search heuristic is proposed and solved for New York City census tracts.•Reduced variance when inputting this data to population synthesis.
While data plays an important role in transportation research, sampled data is not always reliable. Data reliability issue is significant especially for minority groups. In this study, a districting approach is proposed which improves data reliability through aggregation of basic spatial units (BSU), adapted from a max-p-regions problem. The model generates as many aggregated zones as possible that minimize intrazonal heterogeneity while minimizing data margin of error (MOE) of all aggregated zones using a controlling MOE threshold. The problem is first formulated as an integer programming which selects optimal set of zones from a pre-generated set of candidate zones. The difficulty of solving the formulation lies in the generation of the candidate set, so a heuristic solution algorithm is proposed. Two case studies are provided to illustrate the method and validate its performance by evaluating the resulting data quality in an example subsequent planning model. First is an area in Downtown Manhattan with 62 census tracts, comparing the aggregated zones with Neighborhood Tabulation Areas (NTAs) and Taxi Zones. Second is the generation of the New York City Equitable Zoning (NYCEZ), which generated 574 Equitable Zones that reduce the average MOE% of demographic data by 48% for seniors, 75% for low-income population, and 46% for long commuters, all with a district number that is higher than NTAs (221) and Taxi Zones (263). NYCEZ and census tracts are then compared in a subsequent model, synthetic population generation, showing an improvement of 6.2% in standard deviation across simulated populations under the proposed zone design. NYCEZ showed smaller variation in the generated population data. The algorithm can help the decision making of public agencies and the service design of mobility providers by producing reliable and equitable data. The algorithm can also be applied to data-sharing between mobility providers and agencies to alleviate privacy concerns.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Our study introduces a drone routing problem in which drones fly to capture photos for surveillance purposes after a disaster. The drones perform observations on nodes and edges representing ...populated areas and road segments of a network from multiple altitudes. Each target node and edge requires observation at least once with a certain required quality. When the drones fly at a relatively high altitude, they can simultaneously capture low-quality photos and a large number of observed target nodes and edges. However, high-quality photos and narrow observation areas can be captured from a relatively low altitude. Each drone has a limited battery capacity and thus must return to the depot for battery replacement. This study routes the drones to satisfy the required photo quality of all target nodes and edges while minimizing the makespan of the surveillance by all drones. Our study is the first to examine a multiple-drone routing problem while considering flight altitude-dependent observation quality, battery replacement, node and edge combination, and minimizing the makespan. Our problem is formulated as a mixed integer linear programming (MILP) model. Firefly and adaptive-reactive tabu search algorithms are proposed. The latter outperforms the former and obtains better solutions than those in the MILP model for small-sized instances within a given short computation time.
Growing concerns about the climate change have forced governments to initiate tighter environmental regulations and tougher emission reduction targets, increasing the interest on electromobility. ...Logistics operators started employing electric vehicles (EVs) and must face new operational planning challenges. Moreover, with an ever-growing interest in e-commerce, parcel delivery is taking new shapes by offering flexible delivery options to the customers. To mitigate these issues, we introduce the Electric Vehicle Routing Problem with Flexible Deliveries (EVRP-FD), where the customers are served using a fleet of EVs that can recharge their batteries along their routes. In this problem, a customer may specify different delivery locations for different time windows. Our objective is to serve the customers while minimising the total travelled distance using minimum number of vehicles. We first give the mathematical model and then develop a hybrid Variable Neighbourhood Search coupled with Tabu Search by proposing new mechanisms to solve the problem effectively. Then, we verify the performance of our algorithm on instances from the literature. We also introduce new instances for the EVRP-FD and perform an extensive computational study to investigate the trade-offs associated with different operational factors. Finally, we present a case study in Nottingham, UK to provide further insights.
Full text
Available for:
BFBNIB, GIS, IJS, IZUM, KILJ, KISLJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
PDF